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178 results for Machine Learning Engineer jobs

Machine Learning Engineer
  • Herndon, VA
  • onsite
  • Temporary / Contract
  • 70 - 75 USD / Hourly
  • <p><strong>Machine Learning Engineer</strong></p><p><strong>Pay: </strong>$70-75/hr, available solely on W2 Basis</p><p><strong>Consultant I (Contractor)</strong></p><p><strong>Work Location:</strong> Reston, VA (4x onsite)</p><p><strong>Engagement Type: </strong>34 Week Contract, Potential for Extension or Conversion</p><p><strong>Position Overview</strong></p><p>We are seeking a Machine Learning Engineer to support the design, development, and optimization of machine learning solutions for real‑world applications. This role focuses on model development, data pipeline construction, and performance evaluation within a collaborative engineering environment.</p><p><strong>Key Responsibilities</strong></p><ul><li>Design, build, train, and evaluate machine learning and deep learning models for production and analytical use cases</li><li>Develop and maintain scalable data pipelines for data collection, cleaning, transformation, and ingestion</li><li>Conduct experiments and analyze performance metrics such as accuracy, recall, and AUC</li><li>Optimize models for performance, speed, reliability, and scalability</li><li>Collaborate with cross‑functional teams to support data‑driven solutions</li></ul>
  • 2026-08-17T00:00:00Z
Machine Learning Engineer
  • Los Angeles, CA
  • onsite
  • Permanent / Full Time
  • 200000 - 260000 USD / Yearly
  • RESPONSIBILITIES:<br>ML Model Deployment &amp; Platform Management<br>• Lead the design, implementation, and ongoing maintenance of scalable ML infrastructure on Databricks, including ML flow for experiment tracking, model registry, and model serving endpoints.<br>• Oversee the development of the ML Ops platform and automated pipelines for deploying, monitoring, and maintaining models within production environments.<br>• Implement robust solutions for model versioning, systematic retraining, and comprehensive artifact management using Databricks Unity Catalog for ML governance.<br>• Design and manage Databricks Feature Store for consistent feature engineering across training and inference pipelines.<br>Generative AI &amp; LLM Operations<br>• Architect and implement Retrieval-Augmented Generation (RAG) systems for document Q&amp;A, enabling business teams to query fund documents, investor letters, and market research.<br>• Design, deploy, and manage vector database solutions (Databricks Vector Search, Pinecone, or similar) for semantic search and retrieval across enterprise documents.<br>• Lead LLM fine-tuning and customization initiatives, training models like Claude or open-source alternatives with CIM proprietary data while ensuring data privacy and compliance.<br>• Develop and optimize document processing pipelines including PDF parsing, chunking strategies, and embedding generation for RAG applications.<br>• Implement prompt engineering best practices and LLM evaluation frameworks to ensure output quality, relevance, and factual accuracy.<br>• Build guardrails and safety measures for GenAI applications, including hallucination detection, output validation, and source attribution.<br>Automation &amp; CI/CD Pipelines<br>• Design and implement extensive automation across the ML workflow, covering model training, testing, validation, and deployment using Databricks Workflows and Asset Bundles.<br>• Set up robust CI/CD pipelines for both traditional ML models and GenAI applications, leveraging GitHub Actions, Azure DevOps, or similar tools.<br>• Automate complex data and model workflows utilizing orchestration tools such as Airflow, Prefect, or Databricks Workflows.
  • 2026-07-29T00:00:00Z
Machine Learning Engineer
  • Menlo Park, CA
  • onsite
  • Permanent / Full Time
  • 200000 - 300000 USD / Yearly
  • <p><strong>Machine Learning Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>Based in Los Angeles, California, the company specializes in transforming complex, multi-source data into actionable insights through machine learning, knowledge graph technologies, and advanced analytics. This is an opportunity to work on mission-critical applications in a highly collaborative environment focused on innovation, scalability, and operational excellence.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Machine Learning Engineer will play a critical role in designing, training, deploying, and optimizing machine learning models that operate on large-scale temporal, geospatial, relational, and unstructured datasets. This position requires an experienced engineer who can independently own the full machine learning lifecycle, from dataset development and model architecture selection to deployment, monitoring, and continuous improvement. The ideal candidate brings broad expertise across computer vision, natural language processing (NLP), geospatial analytics, MLOps, and large-scale production machine learning environments.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, train, evaluate, deploy, and optimize machine learning models across multiple production use cases.</li><li>Build predictive solutions for anomaly detection, forecasting, entity resolution, relationship prediction, risk assessment, and operational decision support.</li><li>Partner with data engineering teams to develop high-quality training datasets from structured, unstructured, temporal, relational, and geospatial data sources.</li><li>Design model architectures and select appropriate algorithms based on business objectives, data characteristics, and operational requirements.</li><li>Develop and maintain machine learning pipelines spanning data preparation, feature engineering, training, evaluation, deployment, and monitoring.</li><li>Build scalable solutions that leverage graph-based and knowledge graph-driven data architectures.</li><li>Develop models utilizing computer vision, NLP, geospatial analytics, and predictive modeling techniques.</li><li>Establish rigorous evaluation frameworks, baselines, performance metrics, and validation methodologies.</li><li>Design experiments that mitigate data leakage, model drift, bias, and changing data distributions.</li><li>Implement monitoring, observability, alerting, retraining, rollback, and model governance processes.</li><li>Maintain reproducible datasets, model artifacts, evaluation results, and deployment workflows.</li><li>Collaborate with distributed engineering teams to deliver reliable and scalable machine learning capabilities.</li><li>Improve model calibration, confidence scoring, uncertainty estimation, and explainability.</li><li>Contribute to technical architecture, machine learning standards, and long-term platform strategy.</li></ul><p><strong>Additional Details</strong></p><ul><li>Fully onsite 5 days a week</li><li>Highly collaborative environment with strong emphasis on machine learning, knowledge graphs, and data-driven decision support</li><li>Opportunity to influence technical direction, machine learning standards, and model lifecycle practices across multiple initiatives</li><li>Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements</li></ul>
  • 2026-08-19T00:00:00Z
Machine Learning Engineer I (Contractor)
  • Philadelphia, PA
  • remote
  • Temporary / Contract
  • 37 - 42 USD / Hourly
  • We are looking for a Machine Learning Engineer I (Contractor) to join a team building and improving intelligent software solutions. This Long-term Contract position is well suited for someone who enjoys working across model development, data engineering, and production deployment in a hands-on engineering environment. The role offers the opportunity to support both current applications and early-stage concepts by combining technical execution with careful analysis, testing, and documentation.<br><br>Responsibilities:<br>• Build, improve, and verify machine learning algorithms that support product and application objectives.<br>• Create and maintain end-to-end data workflows that handle ingestion, quality checks, cleansing, and ongoing monitoring.<br>• Train machine learning models, measure performance against validation criteria, and release models that meet requirements into production environments.<br>• Contribute to prototype development and exploratory initiatives that help shape future technical solutions.<br>• Prepare and update technical materials such as evaluation plans, reports, presentations, white papers, test summaries, manuals, and Confluence documentation.<br>• Execute testing activities, analyze outcomes, and document findings through case studies and structured reporting.<br>• Partner with engineering and cross-functional teams to translate technical requirements into practical machine learning solutions.
  • 2026-08-20T00:00:00Z
Software Engineer - Data Science
  • Naperville, IL
  • onsite
  • Temporary / Contract
  • 51.4615 - 59.587 USD / Hourly
  • We are looking for a Software Engineer - Data Science to join a growing organization in Naperville, Illinois and help strengthen the platform capabilities that support machine learning and data science initiatives. This Long-term Contract position will partner closely with infrastructure, development, and data-focused teams to build reliable engineering foundations, streamline delivery practices, and improve day-to-day productivity. The ideal candidate brings a strong software engineering background along with experience in cloud environments, automation, and modern deployment workflows.<br><br>Responsibilities:<br>• Design and enhance platform solutions that enable data scientists and machine learning engineers to develop, test, and deploy their work efficiently<br>• Build, maintain, and optimize CI/CD workflows to support dependable releases and consistent engineering standards<br>• Develop automation for infrastructure provisioning and configuration management using infrastructure-as-code approaches<br>• Manage and improve cloud-based resources and services to ensure scalable, secure, and resilient platform operations<br>• Collaborate with engineering and data teams to remove workflow bottlenecks and strengthen the overall developer experience<br>• Support software delivery best practices across the full development lifecycle, from code integration through production deployment<br>• Contribute to application and platform development efforts using technologies such as C#, .NET, ASP.NET, JavaScript, and React.js<br>• Integrate and support data platform components, including Snowflake, within broader engineering solutions
  • 2026-08-19T00:00:00Z
Artificial Intelligence (AI) Engineer
  • Monroe, NY
  • onsite
  • Permanent / Full Time
  • 150000 - 225000 USD / Yearly
  • <p>We are seeking a skilled AI Engineer to join our dynamic technology team. The ideal candidate has hands-on experience integrating advanced AI and large language model (LLM) features into applications, as well as a strong background in designing and delivering AI-driven solutions. In this role, you will work closely with product, engineering, and data teams to build and enhance innovative products using the latest AI frameworks and tools.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><p><br></p><ul><li>Design, develop, and integrate AI and LLM features into new or existing applications, ensuring scalable and reliable deployment.</li><li>Collaborate with cross-functional teams to define technical requirements and deliver AI-driven functionalities in production environments.</li><li>Utilize AI frameworks, APIs, and platforms such as OpenAI, LangChain, vector databases, and machine learning libraries to accelerate solution development.</li><li>Lead prompt engineering, fine-tuning, and model optimization initiatives to improve performance and user outcomes.</li><li>Evaluate and select the most appropriate AI/ML models, tools, and platforms for project needs.</li><li>Conduct documentation, code reviews, testing, and performance monitoring of AI-driven products.</li><li>Stay up to date with advancements in artificial intelligence, generative models, and industry best practices.</li></ul><p><br></p>
  • 2026-08-21T00:00:00Z
Artificial Intelligence (AI) Engineer
  • Tampa, FL
  • onsite
  • Temporary to Hire
  • 0 - 0 USD / Yearly
  • We are looking for a skilled Artificial Intelligence (AI) Engineer to join our team in Tampa, Florida. This role offers the opportunity to design and implement innovative AI solutions while collaborating with cross-functional teams to drive impactful results. As a Contract to permanent position, this role provides a pathway to long-term growth and development within our organization.<br><br>Responsibilities:<br>• Build, train, and refine machine learning models using frameworks such as TensorFlow, PyTorch, Scikit-Learn, and Keras.<br>• Integrate AI-driven solutions into existing on-premises applications to enhance functionality and performance.<br>• Explore and experiment with large language models (LLMs) and agent-based coding tools to optimize internal automation and analytics workflows.<br>• Process, engineer, and evaluate data from diverse internal sources, including structured and unstructured datasets.<br>• Collaborate with teams across departments to ensure compliance with Criminal Justice Information Systems (CJIS) and Personally Identifiable Information (PII) standards.<br>• Partner with analysts, investigators, and IT staff to identify opportunities where AI can provide operational improvements.<br>• Participate in coding reviews and testing processes to ensure high-quality deliverables.<br>• Stay updated on emerging AI technologies and prototype new tools while adhering to data governance standards.<br>• Contribute to the continuous improvement of AI systems and processes by identifying areas for innovation and optimization.
  • 2026-08-19T00:00:00Z
Artificial Intelligence (AI) Engineer
  • West Palm Beach, FL
  • onsite
  • Permanent / Full Time
  • 180000 - 220000 USD / Yearly
  • We are looking for an Artificial Intelligence (AI) Engineer to create and scale enterprise AI solutions in West Palm Beach, Florida. This role focuses on building production-ready applications and shared AI services across cloud environments, with an emphasis on reliability, security, and measurable business value. The ideal candidate will combine strong engineering expertise with practical experience in large language models, automation, and system integration to advance research, knowledge management, and operational efficiency.<br><br>Responsibilities:<br>• Create, implement, and launch enterprise AI applications using Amazon Web Services and related cloud technologies.<br>• Develop scalable AI infrastructure with services such as Amazon Bedrock, SageMaker, EC2, S3, Lambda, API management tools, orchestration services, and monitoring platforms.<br>• Architect AI environments that prioritize security, resilience, performance, and cost control for enterprise use cases.<br>• Build and support reusable AI capabilities that can be adopted across multiple business applications and future informatics efforts.<br>• Engineer solutions powered by large language models, retrieval-augmented generation, AI agents, and contemporary AI development frameworks.<br>• Deliver intelligent assistants, enterprise and semantic search tools, knowledge management capabilities, and document understanding solutions.<br>• Design AI-driven automation that improves workflows and streamlines day-to-day business operations.<br>• Integrate AI platforms with Microsoft and enterprise technologies, including Azure OpenAI, Microsoft 365 Copilot, Copilot Studio, SharePoint Online, Microsoft Teams, and Microsoft Graph.<br>• Develop APIs and connected services that link AI platforms with scientific applications, cloud ecosystems, and business systems.<br>• Contribute to AI governance, lifecycle management, observability, and the evaluation of emerging technologies while helping define enterprise standards and best practices.
  • 2026-08-14T00:00:00Z
Artificial Intelligence (AI) Engineer
  • Atlanta, GA
  • onsite
  • Temporary / Contract
  • 43.5385 - 55.25 USD / Hourly
  • <p>We are looking for an Artificial Intelligence (AI) Engineer to create and expand advanced AI solutions that support real-world business applications in Atlanta, Georgia. This position is ideal for a hands-on engineer who can turn emerging AI concepts into reliable production systems, from intelligent workflows to scalable backend services. The role blends applied machine learning, large language model integration, and software engineering to deliver secure, high-performing tools in an enterprise setting.</p><p><br></p><p>Responsibilities:</p><p>• Design and develop AI-driven applications that combine machine learning models, large language models, and backend services for production use.</p><p>• Create prompt frameworks, retrieval approaches, and context-handling strategies that improve the relevance and reliability of AI-generated outputs.</p><p>• Build intelligent agents and automated workflows that support business processes and interact effectively with enterprise data sources.</p><p>• Integrate tools such as TensorFlow, vector databases, and orchestration frameworks to support scalable AI and computer vision solutions.</p><p>• Measure model and system effectiveness by monitoring accuracy, latency, stability, and overall operational performance.</p><p>• Improve deployed solutions through performance tuning, cost optimization, and troubleshooting across cloud-based environments.</p><p>• Collaborate with product, engineering, and user experience teams to deliver AI features that align with business goals and user needs.</p><p>• Contribute reusable components, shared services, and engineering best practices that strengthen the broader AI platform.</p><p>• Support detection and computer vision use cases where image-based analysis and machine learning capabilities are required.</p>
  • 2026-08-21T00:00:00Z
Artificial Intelligence (AI) Engineer
  • Knoxville, TN
  • remote
  • Permanent / Full Time
  • 0 - 0 USD / Yearly
  • <p>Robert Half is hiring for a Principal level Software Engineer to focus on agentic workflows and AI software products. In this role, you will lead full product development efforts while creating intelligent, scalable applications that combine agentic AI capabilities with modern web technologies. The position calls for a hands-on engineer who can build reliable backend systems, contribute to user-facing experiences, and partner across teams to deliver secure, high-performing solutions.</p><p><br></p><p>Responsibilities:</p><p>• Lead the full software development lifecycle for AI-enabled products, from technical planning and architecture through deployment and ongoing improvement.</p><p>• Create and refine agentic AI workflows that support business objectives and integrate effectively with application services.</p><p>• Build, test, and support scalable server-side applications using Python frameworks such as Django, Flask, or FastAPI, or Node.js frameworks including Express or NestJS.</p><p>• Develop and maintain RESTful or GraphQL interfaces that enable dependable communication between applications and services.</p><p>• Contribute to front-end development with React, ensuring smooth interaction between user interfaces and backend functionality.</p><p>• Architect and support microservices-based and distributed systems designed for reliability, flexibility, and growth.</p><p>• Improve overall system efficiency by tuning application performance, refining database access patterns, and managing cloud resource consumption.</p><p>• Apply strong security practices by implementing access control, authentication, and authorization measures across applications.</p><p>• Oversee containerized delivery processes and automated deployment workflows using Docker and CI/CD tools, while diagnosing and resolving production issues in cloud environments.</p><p>• Work closely with product, design, and DevOps partners to deliver maintainable, well-documented solutions that meet project goals.</p>
  • 2026-08-13T00:00:00Z
Artificial Intelligence (AI) Engineer
  • Knoxville, TN
  • remote
  • Permanent / Full Time
  • 0 - 0 USD / Yearly
  • <p>Robert Half is hiring! We are looking for a Sr/Lead/Principal Engineer that has experience in agentic workflows. This role focuses on building intelligent, production-ready applications that combine modern AI capabilities with reliable full-stack engineering. The ideal candidate will contribute across architecture, development, deployment, and operational support while partnering closely with product, design, and infrastructure teams.</p><p><br></p><p>Responsibilities:</p><p>• Lead complete product delivery efforts, guiding solutions from concept and design through deployment and ongoing improvement.</p><p>• Create and refine agentic AI workflows that support practical business use cases and integrate effectively with broader application ecosystems.</p><p>• Develop scalable server-side applications using Python frameworks such as Django, Flask, or FastAPI, or with Node.js frameworks including Express or NestJS.</p><p>• Build and support RESTful and GraphQL interfaces that enable secure, efficient communication between services and user-facing applications.</p><p>• Enhance front-end experiences in React, ensuring strong connectivity between interface components and backend systems.</p><p>• Architect and maintain microservices and distributed application components with a focus on reliability, scalability, and maintainability.</p><p>• Improve system efficiency by tuning application performance, refining database interactions, and managing cloud resource consumption responsibly.</p><p>• Apply strong security practices by implementing access controls, authentication methods, and authorization standards across the platform.</p><p>• Support automated delivery processes through CI/CD pipelines and containerized deployments using Docker and related tooling.</p><p>• Investigate, troubleshoot, and resolve production issues in cloud environments while collaborating with cross-functional stakeholders.</p>
  • 2026-07-24T00:00:00Z
Artificial Intelligence (AI) System Engineer
  • Albuquerque, NM
  • onsite
  • Permanent / Full Time
  • 0 - 0 USD / Yearly
  • <p>We are looking for an Artificial Intelligence (AI) Engineer to support the design, deployment, and ongoing operation of AI systems for a government services organization in Albuquerque, New Mexico. This position centers on building reliable AI infrastructure, enabling machine learning solutions in production, and partnering with cross-functional teams to deliver secure, scalable platforms. </p><p>The ideal candidate brings strong experience in automation, Kubernetes-based deployments, and modern MLOps practices, along with the ability to translate technical needs into durable operational solutions.</p><p><br></p><p>Responsibilities:</p><p>• Direct the rollout and integration of AI platforms and services, ensuring they work effectively with existing enterprise technologies and operational standards.</p><p>• Architect, implement, and refine AI infrastructure in partnership with cloud, server, and platform engineering teams to support dependable system performance.</p><p>• Move machine learning solutions from development into production by establishing repeatable processes for deployment, maintenance, and long-term support.</p><p>• Create and manage CI/CD and MLOps workflows that cover model validation, packaging, release, rollback, and lifecycle oversight.</p><p>• Automate infrastructure and platform operations through scripting, infrastructure-as-code methods, and configuration management tools.</p><p>• Troubleshoot platform and service issues, perform root cause analysis, and produce clear technical documentation for support and maintenance activities.</p><p>• Strengthen system visibility by implementing logging, monitoring, alerting, and incident response practices across AI environments.</p><p>• Uphold security and compliance expectations by contributing to audits, remediation efforts, vulnerability management, and secure design reviews.</p><p>• Identify and deliver improvements that increase performance, scalability, reliability, and cost efficiency across AI-enabled systems.</p><p>• Work with technical and business stakeholders to align AI implementations with organizational priorities and evaluate emerging tools for long-term operational value.</p><p>Other duties as needed</p>
  • 2026-08-10T00:00:00Z
Data & ML Platform Engineer Manager
  • Inglewood, CA
  • onsite
  • Permanent / Full Time
  • 180000 - 200000 USD / Yearly
  • <p><strong>Job Title</strong></p><p>Manager, Data &amp; Machine Learning Platform Engineer</p><p><br></p><p><strong>Company Overview</strong></p><p>A leading organization in the sports and entertainment industry is redefining the live event and fan engagement experience through data and AI. By leveraging cutting-edge technology and advanced analytics, the organization is building innovative platforms that deliver personalized, seamless experiences for millions of fans.</p><p><br></p><p><strong>Role Summary</strong></p><p>This Los Angeles-based role is a hands-on opportunity for a Manager, Data &amp; Machine Learning Platform Engineer to design and build end-to-end data and ML systems that power intelligent products across fan engagement, marketing, and operations. Acting as an individual contributor, you will own the full lifecycle of data and machine learning platforms—from data ingestion to real-time model deployment—enabling scalable, production-ready AI solutions.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, build, and maintain scalable data pipelines and ML platform infrastructure for analytics and AI use cases</li><li>Own the end-to-end lifecycle of data and ML systems, including ingestion, transformation, feature engineering, deployment, and monitoring</li><li>Develop and optimize data models and schemas to support both batch and real-time workflows</li><li>Build and manage feature pipelines and enable low-latency access for real-time decisioning systems</li><li>Deploy machine learning models into production via APIs and real-time inference services</li><li>Implement CI/CD pipelines for machine learning workflows, including testing, versioning, and automated deployment</li><li>Establish monitoring systems to track data quality, model performance, and system reliability</li><li>Enable experimentation frameworks such as A/B testing to support data-driven product iteration</li><li>Collaborate cross-functionally with data scientists, product teams, and business stakeholders to deliver impactful AI solutions</li><li>Drive architectural decisions and promote best practices in data engineering and MLOps</li></ul><p><strong>Compensation &amp; Benefits</strong></p><ul><li>$180,000 – $200,000</li><li>Comprehensive benefits package including medical, dental, and vision coverage</li><li>401(k) with company contribution</li><li>Annual wellbeing allowance</li><li>Flexible paid time off and parental leave</li><li>Company-paid life and disability insurance</li><li>Mental health and wellness support programs</li><li>Flexible spending accounts and family planning assistance</li></ul><p><strong>Additional Details</strong></p><ul><li>Work model: Hybrid (4 days onsite per week)</li><li>Core working hours with flexibility</li><li>Individual contributor role (no direct reports)</li><li>High-impact role contributing to enterprise-wide AI initiatives</li></ul>
  • 2026-08-13T00:00:00Z
Data and Knowledge Engineer
  • Menlo Park, CA
  • onsite
  • Permanent / Full Time
  • 200000 - 300000 USD / Yearly
  • <p><strong>Data &amp; Knowledge Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading artificial intelligence and advanced analytics organization is seeking a Data &amp; Knowledge Engineer to help power next-generation AI and decision-support platforms. Based in Los Angeles, California, the company specializes in integrating complex data from disparate sources into unified intelligence systems that support advanced analytics, automation, and operational decision-making. This is an opportunity to work on mission-critical initiatives involving large-scale data, knowledge graphs, and AI-driven applications.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Data &amp; Knowledge Engineer will lead the onboarding, transformation, and governance of complex multimodal data into scalable data and knowledge platforms. This role focuses on integrating structured and unstructured data sources, designing reusable data pipelines, developing entity resolution frameworks, and enabling high-quality data for analytics, retrieval, AI workflows, and geospatial applications. The ideal candidate combines strong data engineering expertise with experience in knowledge graphs, data quality, and large-scale information management.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design and develop scalable data ingestion pipelines for structured, unstructured, geospatial, and sensor-based data sources.</li><li>Build and maintain batch and streaming data processing systems across cloud, on-premises, and disconnected environments.</li><li>Develop integrations with APIs, databases, file systems, enterprise applications, and external data sources.</li><li>Design schema mapping, normalization, and transformation processes that support diverse customer data models.</li><li>Implement entity resolution, record linkage, deduplication, and data matching capabilities across multiple sources.</li><li>Preserve data lineage, provenance, auditing, and traceability throughout the data lifecycle.</li><li>Create data validation, monitoring, replay, and exception-handling processes for complex data environments.</li><li>Develop workflows for managing ambiguous records, conflicting information, and data quality issues.</li><li>Define and measure data quality metrics, onboarding effectiveness, and operational performance indicators.</li><li>Support knowledge graph, retrieval, AI, and analytics capabilities through high-quality governed datasets.</li><li>Partner with engineering and stakeholder teams to transform recurring onboarding requirements into reusable platform capabilities.</li><li>Contribute to platform architecture, engineering standards, and long-term data strategy initiatives.</li></ul><p><strong>Additional Details</strong></p><ul><li>Fully onsite 5 days a week</li><li>Full-time exempt position</li><li>Hands-on engineering role with substantial ownership and technical influence</li><li>Opportunity to work on large-scale data, knowledge graph, and AI-driven initiatives</li><li>Staff-level candidates may provide architectural leadership, mentorship, and engineering guidance</li><li>Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements</li></ul>
  • 2026-08-19T00:00:00Z
Full Stack AI Engineer
  • Dublin, OH
  • onsite
  • Temporary / Contract
  • 75 - 80 USD / Hourly
  • <p>We are looking for a Full Stack AI Engineer for a long-term consultant position. This role is responsible for designing, building, and delivering end-to-end intelligent applications and agentic AI systems that enable automation, decision-making, and enhanced user experiences across our client&#39;s enterprise landscape.</p><p> </p><p>This role combines full-stack software engineering with applied AI to develop systems that can reason, plan, and execute tasks autonomously. The engineer partners with product, architecture, and business teams to translate complex requirements into scalable, production-ready solutions that integrate seamlessly with enterprise platforms, data, and processes.</p><p> </p><p>The position emphasizes hands-on development, system integration, and continuous delivery of business value, ensuring AI-enabled capabilities are reliable, secure, and aligned with enterprise standards while advancing innovation and operational efficiency.</p>
  • 2026-08-18T00:00:00Z
Data Engineer
  • Kalamazoo, MI
  • remote
  • Permanent / Full Time
  • 150000 - 225000 USD / Yearly
  • We are looking for a senior-level Data Engineer to shape and deliver a scalable data platform in Kalamazoo, Michigan. This role combines strategic architecture with hands-on engineering, creating reliable data products that support reporting, advanced analytics, and AI-driven solutions. The ideal candidate will build secure, multi-tenant data capabilities with strong attention to privacy, governance, and long-term platform quality.<br><br>Responsibilities:<br>• Lead the design of a modern data platform that supports ingestion, transformation, storage, and consumption across analytical and operational use cases.<br>• Build and maintain robust batch and streaming pipelines that move data from relational systems, object storage, document databases, and event sources into centralized platforms.<br>• Define data architecture standards, modeling approaches, and engineering practices that improve consistency, reliability, and scalability across the organization.<br>• Create multi-tenant data solutions with strong isolation controls, secure access patterns, and governance measures built into the platform design.<br>• Develop data models and serving layers that enable enterprise reporting, self-service analytics, and AI or machine learning workloads.<br>• Evaluate cloud-based data services, processing frameworks, and warehouse technologies to ensure the platform meets performance, cost, and security expectations.<br>• Partner with product, engineering, and leadership teams to explain technical decisions, highlight risks, and align platform investments with business priorities.<br>• Oversee external vendors and implementation partners by reviewing recommendations, challenging misaligned approaches, and enforcing internal data standards.
  • 2026-08-04T00:00:00Z
Data Engineer
  • Austin, TX
  • onsite
  • Temporary / Contract
  • 50 - 55 USD / Hourly
  • <p><strong>Robert Half</strong> is actively partnering with an Austin-based client to identify a Data Engineer <strong>(contract).</strong> In this role, you will support enterprise data initiatives and help build scalable data solutions that drive operational efficiency and business insights. This role will partner closely with business stakeholders, analysts, and technical teams to design, develop, and maintain data integrations that support reporting, analytics, and decision-making across the organization. <strong>This role is onsite in Austin, Tx. </strong></p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li>Build and maintain data pipelines and integration processes across multiple systems and data sources.</li><li>Translate business requirements into scalable technical solutions.</li><li>Develop and maintain data architecture, integration, and process documentation.</li><li>Monitor, troubleshoot, and optimize data pipeline performance and reliability.</li><li>Partner with cross-functional teams to deliver high-quality data solutions.</li><li>Ensure data quality through validation, monitoring, and error-handling processes.</li><li>Resolve data-related issues and perform root-cause analysis.</li><li>Participate in code reviews, performance tuning, and continuous improvement initiatives.</li><li>Collaborate with analysts, developers, and business users to support reporting and analytics needs.</li><li>Contribute to shared data models, standards, and governance efforts.</li></ul>
  • 2026-08-07T00:00:00Z
Data Engineer
  • Southborough, MA
  • remote
  • Temporary / Contract
  • 63.3365 - 73.337 USD / Hourly
  • <p>We are looking for a Data Engineer to join a long-term, 100% remote contract opportunity. This role will focus on strengthening and modernizing the organization’s reporting environment by improving how data is collected, connected, transformed, and presented through Power BI. The ideal candidate will bring strong hands-on experience building enterprise-grade data solutions and will be comfortable working independently in an environment that values initiative, problem-solving, and practical execution.</p><p><br></p><p>Responsibilities:</p><p>• Design and enhance data pipelines that move information reliably across systems and support accurate business reporting.</p><p>• Integrate data from multiple internal and external sources so platforms communicate effectively and deliver consistent outputs.</p><p>• Refine and elevate existing Power BI solutions by improving data models, report performance, usability, and visualization quality.</p><p>• Establish automated data refresh schedules and workflow orchestration to support timely and dependable reporting operations.</p><p>• Build scalable transformation processes that prepare raw data for downstream analytics, dashboards, and operational insights.</p><p>• Connect and manage end-to-end data flows to ensure information is routed to the proper destinations with strong data integrity.</p><p>• Apply enterprise data engineering practices, including medallion architecture and Microsoft Fabric capabilities, to support a sustainable analytics framework.</p><p>• Partner with stakeholders to identify gaps, propose effective solutions, and implement improvements with minimal oversight in a fast-moving environmen</p>
  • 2026-08-19T00:00:00Z
Data Engineer
  • Boston, MA
  • onsite
  • Temporary / Contract
  • 39.5865 - 45.837 USD / Hourly
  • We are looking for a Data Engineer to support enterprise data movement and application integration efforts in Boston, Massachusetts. This Long-term Contract position will focus on building, maintaining, and enhancing custom services that transfer, load, and transform data across multiple systems. The role works closely with technical and business teams to deliver reliable integration solutions using .NET/C#, APIs, and modern deployment practices.<br><br>Responsibilities:<br>• Design, support, and improve custom integration services that move data between enterprise platforms and applications.<br>• Build and maintain ETL processes for data loading, transformation, and system-to-system exchange.<br>• Develop microservice-based solutions in .NET/C# to replace larger legacy integration components where needed.<br>• Create and support API-driven integrations, including services that rely on REST and SOAP protocols.<br>• Partner with business analysts, developers, and solution stakeholders to translate operational needs into technical data workflows.<br>• Monitor data pipelines and integration jobs, troubleshoot failures, and resolve performance or reliability issues.<br>• Contribute to deployment and release activities using Azure DevOps or comparable CI/CD tools.<br>• Support integrations involving key enterprise platforms such as Salesforce and higher education systems when applicable.
  • 2026-08-19T00:00:00Z
Data Engineer
  • Erlanger, KY
  • onsite
  • Temporary / Contract
  • 38 - 44 USD / Hourly
  • <p>We are looking for a detail-focused Engineer/Analyst to join a Long-term Contract assignment supporting technical data quality and material information management in northern Kentucky. In this role, you will help maintain accurate, standardized data for raw materials and packaging components so teams can move product development, supplier onboarding, and manufacturing activities forward efficiently. This position works closely with research, quality, procurement, operations, and master data partners to strengthen consistency across systems and improve the reliability of material records. This role will be onsite 4 days a week and 1 day remote. Must be comfortable working in a lab/plant manufacturing setting. YOU MUST LIVE IN KY or OH to be considered. No option for remote work.</p><p><br></p><p>Responsibilities:</p><p>• Manage the collection, review, and entry of technical specifications for raw materials and packaging components within designated data and specification platforms.</p><p>• Verify that material records are complete, accurate, and aligned with company standards, compliance expectations, and approved documentation.</p><p>• Apply consistent naming structures, formatting rules, and data standards to improve usability across regional and enterprise systems.</p><p>• Investigate missing, conflicting, or outdated information in material specifications and resolve issues through coordination with cross-functional stakeholders.</p><p>• Maintain material master records and ensure proper connections between specification data, system entries, and related documentation.</p><p>• Build, revise, and validate bills of materials to support production readiness, product updates, supplier changes, and ongoing improvement efforts.</p><p>• Partner with master data, procurement, operations, and technical teams to enhance data governance practices and streamline data management processes.</p><p>• Monitor assigned project activities and data deliverables to help keep timelines on track and support broader documentation standardization efforts.</p>
  • 2026-08-21T00:00:00Z
Data Engineer
  • San Francisco, CA
  • remote
  • Temporary / Contract
  • 65 - 70 USD / Hourly
  • <p>We are looking for a Contract Data Engineer to support financial systems and data operations in San Francisco, California. This is a remote on-going contract. This role will work across Finance, Systems, and Engineering to improve data reliability, strengthen integrations, and enhance platforms that support billing, accounts payable, and quote-to-cash workflows. The ideal candidate brings deep technical expertise with NetSuite and Snowflake, along with strong coding skills to diagnose issues, streamline processes, and build scalable solutions in a complex systems environment.</p><p><br></p><p>Responsibilities:</p><p>• Build, monitor, and refine data pipelines that move financial and transactional information across internal platforms and enterprise systems.</p><p>• Investigate data issues, resolve integration failures, and improve the overall accuracy and consistency of business-critical datasets.</p><p>• Develop and maintain middleware solutions that connect NetSuite, Salesforce, Snowflake, and custom applications.</p><p>• Partner with Finance, Systems, and Engineering stakeholders to deliver technical enhancements that support accounting operations and downstream reporting.</p><p>• Implement improvements within NetSuite and related financial systems to better support billing, accounts payable, and quote-to-cash processes.</p><p>• Troubleshoot code and system behaviors using SQL, Python, and related tools to identify root causes and restore reliable performance.</p><p>• Support integration workflows between Salesforce and NetSuite, ensuring stable data exchange and operational continuity.</p><p>• Evaluate and contribute to automation initiatives, including AI-enabled workflow opportunities that can reduce manual effort and improve efficiency.</p>
  • 2026-08-19T00:00:00Z
Data Engineer
  • Los Angeles, CA
  • onsite
  • Permanent / Full Time
  • 130000 - 140000 USD / Yearly
  • <p><strong>Data Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading food manufacturing and distribution organization is seeking a Data Engineer to support enterprise data initiatives and drive business intelligence capabilities. Based in Los Angeles, California, the company serves a large network of customers through innovative operations, quality-focused processes, and data-driven decision making. This is an opportunity to join a collaborative team where technology and analytics play a critical role in business growth and operational excellence.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines that support reporting, analytics, and business operations. This role will partner closely with analysts and cross-functional stakeholders to transform raw data into reliable, actionable insights. The ideal candidate brings experience in manufacturing or food production environments and possesses strong expertise in data warehousing, ETL development, cloud technologies, and reporting platforms.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, and maintain scalable ETL and ELT data pipelines.</li><li>Build and optimize data workflows that consolidate information from multiple business systems.</li><li>Partner with business stakeholders and analysts to translate data requirements into technical solutions.</li><li>Develop and maintain data models and warehouse structures to support reporting and analytics.</li><li>Monitor, troubleshoot, and enhance data pipelines to ensure data accuracy, integrity, and availability.</li><li>Optimize data storage and retrieval processes for performance, scalability, and reliability.</li><li>Support business intelligence initiatives by delivering clean, trusted datasets for reporting and dashboards.</li><li>Create and maintain technical documentation for data architecture, processes, and workflows.</li><li>Collaborate with engineering, analytics, and business teams to drive data-driven decision making.</li><li>Stay current on emerging technologies and best practices in data engineering and analytics.</li></ul><p><strong>Additional Details</strong></p><ul><li>Work model: On-site for the first 90 days, transitioning to a hybrid schedule thereafter</li><li>Join a team of analytics professionals supporting enterprise reporting and data initiatives</li><li>Opportunity to have a direct impact on operational and business performance through data solutions</li></ul>
  • 2026-08-20T00:00:00Z
Data Engineer
  • Atlanta, GA
  • onsite
  • Permanent / Full Time
  • 140000 - 145000 USD / Yearly
  • We are looking for an experienced Data Engineer to join our team in the Metro Atlanta area. This role will focus on designing, developing, and optimizing data pipelines within a modern Azure cloud environment. The ideal candidate will have strong hands-on experience with Azure and Databricks, excellent problem-solving abilities, and the ability to work closely with Data Scientists and business stakeholders to deliver reliable, scalable data solutions. <br> Responsibilities: • Design, develop, maintain, and optimize scalable data pipelines and ETL/ELT processes. • Troubleshoot data pipelines that are missing SLAs by identifying bottlenecks and implementing solutions to improve performance and processing efficiency. • Work with large volumes of structured and unstructured data while maintaining strong data quality and reliability. • Develop and optimize data solutions using Python, SQL, PySpark, Azure, and Databricks. • Build and manage Databricks pipelines and workflows within a production environment. • Rework and improve existing data structures to support analytics, forecasting, and machine learning initiatives. • Partner closely with Data Scientists to develop and maintain data pipelines supporting predictive modeling and machine learning projects. • Analyze existing data environments and proactively identify opportunities to improve performance, reliability, and data quality. • Collaborate with technical teams and business stakeholders to understand requirements and translate complex data concepts into practical solutions. • Communicate effectively with customers and stakeholders, including those without a technical background. • Work independently in a fast-paced environment while adapting to changing priorities and project requirements. • Apply strong critical thinking and analytical skills to solve complex data engineering challenges. • Support data governance and data management best practices across the organization. • Utilize DevOps practices and tools, including Azure DevOps, to support efficient development and deployment processes. • Contribute to the development of modern data and analytics capabilities that support business intelligence, forecasting, and AI initiatives.
  • 2026-08-19T00:00:00Z
Data Engineer
  • Madison, WI
  • onsite
  • Temporary to Hire
  • 66.5 - 77 USD / Hourly
  • We are looking for a Data Engineer to join a contract opportunity with permanent potential, supporting data-intensive work in Madison, Wisconsin. This role focuses on building and optimizing modern data solutions that enable scientific and business teams to access reliable, scalable information. The ideal candidate brings deep experience with cloud-based engineering, strong Databricks expertise, and the ability to work across technical and research-focused stakeholders.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines that ingest, transform, and deliver complex datasets for analytics and reporting.<br>• Develop and optimize Databricks solutions using Python, Spark, PySpark, and Delta Lake to support high-performance data processing.<br>• Create and enhance cloud-based data architecture in Azure, ensuring reliability, maintainability, and efficient data access.<br>• Partner with cross-functional teams in IT, science, and business to translate research and operational needs into effective data engineering solutions.<br>• Implement data models and warehousing structures that improve reporting accuracy, usability, and long-term scalability.<br>• Manage integration of biological, genomic, or other life sciences data sources while preserving data quality and consistency.<br>• Write and refine database objects such as queries, stored procedures, and functions to support downstream applications and analysis.<br>• Contribute to Agile delivery practices by participating in planning, prioritization, and iterative solution development.
  • 2026-08-19T00:00:00Z
Data Engineer
  • Cincinnati, OH
  • onsite
  • Temporary / Contract
  • 67.45 - 78.1 USD / Hourly
  • We are looking for a Data Engineer to support scalable data solutions for a Long-term Contract position based in Cincinnati, Ohio. This role focuses on building reliable data pipelines, optimizing data movement across platforms, and enabling efficient access to high-quality datasets for business and technical teams. The ideal candidate brings strong hands-on experience with modern big data tools and a practical approach to designing robust ETL workflows.<br><br>Responsibilities:<br>• Design and maintain end-to-end data pipelines that process large and complex datasets with a focus on performance and reliability.<br>• Develop ETL workflows using Python and Spark to transform raw data into structured, usable formats for downstream consumption.<br>• Work with Hadoop-based environments to manage distributed data processing and storage activities at scale.<br>• Integrate streaming and messaging components such as Kafka to support near real-time data ingestion and event-driven processing.<br>• Monitor pipeline health, troubleshoot data issues, and implement improvements that strengthen stability and data quality.<br>• Collaborate with analysts, developers, and other stakeholders to understand data needs and translate them into technical solutions.<br>• Improve existing data architecture by refining workflows, reducing processing bottlenecks, and increasing operational efficiency.
  • 2026-08-19T00:00:00Z
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