<p><strong>Robert Half is working with a client who is looking to hire a Machine Learning Engineer</strong> to help operationalize machine learning models as part of a growing enterprise AI program.</p><p>This role will sit between Data Science and Engineering and will focus on taking models from experimentation into reliable, scalable production environments.</p><p>Responsibilities</p><ul><li>Develop and deploy machine learning models into production.</li><li>Build reusable ML pipelines for training, testing, deployment, and monitoring.</li><li>Partner with Data Scientists to productionize predictive models.</li><li>Develop APIs and services that expose machine learning capabilities to enterprise applications.</li><li>Monitor model performance, drift, and reliability.</li><li>Build automated testing and deployment processes for ML workloads.</li><li>Optimize model performance and infrastructure utilization.</li><li>Work with Data Engineering teams to establish reliable training and inference datasets.</li></ul><p><br></p>
<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>
<p>As our portfolio of AI-driven solutions continues to expand, we’re looking for an experienced Machine Learning Engineer to join our high-impact data science team. This role offers the opportunity to work across trading, operations, and support functions—delivering production-grade machine learning systems that solve real business problems.</p><p>You’ll collaborate with data scientists, software engineers, and commercial stakeholders to design, build, and deploy models that drive decision-making and innovation. From project scoping to model deployment, you’ll have visibility and influence across the full ML lifecycle.</p><p>🔧 Core Responsibilities</p><ul><li>Act as a thought partner to commercial teams, identifying high-value opportunities for AI/ML applications</li><li>Lead the design, development, and deployment of machine learning systems, with a focus on NLP, LLMs, and Generative AI</li><li>Prioritize projects based on business impact and evolving market conditions</li><li>Collaborate with cross-functional teams to gather requirements and align solutions with strategic goals</li><li>Integrate ML solutions—including GenAI—into existing platforms to ensure seamless user experiences and scalable adoption</li><li>Participate in code reviews, experiment design, and tooling decisions to maintain high engineering standards</li><li>Share knowledge and mentor colleagues to build machine learning fluency across the organization</li></ul>
We are looking for an experienced Artificial Intelligence (AI) Engineer to create practical, scalable AI solutions that help improve business performance and streamline operations in Brookfield, Wisconsin. In this role, you will partner with technical teams and business leaders to turn complex challenges into intelligent applications, machine learning systems, and generative AI capabilities. The ideal candidate brings a strong software engineering foundation along with hands-on experience delivering AI solutions in cloud environments.<br><br>Responsibilities:<br>• Build and implement AI, machine learning, and generative AI solutions that address business and operational needs.<br>• Develop intelligent applications such as virtual assistants, chatbot experiences, copilots, and automated workflows.<br>• Train, evaluate, and refine machine learning models to improve performance, reliability, and business impact.<br>• Create and support retrieval-augmented generation solutions and related applications for knowledge-driven use cases.<br>• Work closely with stakeholders to uncover opportunities where AI can enhance processes, decision-making, and user experiences.<br>• Connect AI capabilities with enterprise systems and cloud-based platforms to enable practical adoption at scale.<br>• Establish model deployment and support practices, including monitoring, governance, and lifecycle management.<br>• Apply security, compliance, and responsible AI standards throughout solution design, development, and release.<br>• Research new AI tools and technologies and recommend options that align with organizational goals.<br>• Produce clear technical documentation covering solution architecture, workflows, and implementation details.
We are looking for an experienced Lead Artificial Intelligence (AI) Engineer to guide the design and delivery of advanced AI solutions for a growing construction-focused organization in Avon, Minnesota. This role will lead the creation of scalable applications that turn complex project and operational data into practical, production-ready tools. The ideal candidate brings strong technical leadership, deep hands-on engineering expertise, and a track record of building reliable AI systems that integrate with enterprise platforms.<br><br>Responsibilities:<br>• Lead the technical direction, architecture, and full lifecycle delivery of a core software platform from early concept through production deployment and ongoing improvement.<br>• Design and develop production-grade AI applications, including retrieval-based solutions, agent-driven workflows, tool orchestration, and review processes that incorporate human oversight.<br>• Create robust evaluation frameworks and context management approaches to improve model quality, system reliability, and business relevance.<br>• Connect AI capabilities with enterprise platforms such as Procore, Salesforce, Bluebeam, financial systems, and the organization’s Microsoft Fabric data environment.<br>• Define and enforce engineering best practices across the AI team, including codebase organization, testing strategy, release management, and operational readiness.<br>• Establish observability standards and monitor usage patterns, performance trends, and solution costs to support stable and efficient production systems.<br>• Partner with cross-functional stakeholders to translate construction and project data into practical AI-enabled workflows and decision-support tools.<br>• Ensure security and governance considerations are embedded throughout solution design, deployment, and ongoing maintenance.
We are looking for a Senior MLOps Engineer to strengthen our machine learning infrastructure in King of Prussia, Pennsylvania. This hybrid position will focus on building dependable systems that support the full model lifecycle, from data preparation and training to deployment and ongoing performance oversight. The role works closely with machine learning and engineering partners to improve reliability, scalability, and cost efficiency across production ML operations.<br><br>Responsibilities:<br>• Lead the design, maintenance, and enhancement of the machine learning platform that supports experimentation, training workflows, model versioning, deployment, and production observability.<br>• Develop and operate resilient data pipelines for model training and live inference, including processes for replaying historical data, recovering from source interruptions, and handling delayed or inconsistent inputs.<br>• Establish data handling practices that preserve time-accurate training sets so models are built on information available at the correct point in time.<br>• Create repeatable pathways for promoting validated models into production while maintaining consistency, traceability, and operational stability.<br>• Implement standards that make training runs reproducible, allowing teams to reliably compare results and investigate performance changes.<br>• Track model behavior in production over time, including delayed outcome validation, and surface issues that affect model quality or business impact.<br>• Optimize infrastructure and workflows to manage compute and data costs as usage expands across larger datasets and multiple deployed models.<br>• Collaborate with ML engineers on model assessment, production readiness, and technical decision-making related to deployment strategies and platform improvements.<br>• Contribute to architecture planning and recommend enhancements to the broader ML and operational ecosystem using sound engineering practices.<br>• Support cloud-native operations using AWS, Kubernetes, Terraform, and Ansible to maintain scalable and well-managed environments.
We are looking for an Artificial Intelligence (AI) Engineer to help build and expand practical AI capabilities for the business. This role works closely with functional leaders to uncover meaningful use cases, convert operational challenges into scalable technical solutions, and deliver tools that improve decision-making and efficiency. It is a strong opportunity for a hands-on specialist who enjoys working in a developing environment and wants to influence how AI is applied across the organization.<br><br>Responsibilities:<br>• Partner with business leaders to understand operational pain points and identify where AI can create measurable value.<br>• Translate business needs into solution concepts, technical approaches, and implementable AI initiatives.<br>• Design, develop, test, and deploy AI and machine learning applications that address real-world business problems.<br>• Evaluate repetitive workflows and manual tasks across departments to recommend automation or intelligent assistance opportunities.<br>• Collaborate with teams such as finance, recruiting, and operations to create tools that improve productivity and information flow.<br>• Help establish an internal pipeline of AI initiatives by assessing impact, feasibility, and implementation priorities.<br>• Serve as a bridge between non-technical stakeholders and technical execution by clearly communicating options, risks, and outcomes.<br>• Contribute to the growth of the organization’s AI capability through hands-on development, experimentation, and continuous improvement.
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.
<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>
We are looking for a Computer Vision Engineer to join a growing team building AI-driven solutions for manufacturing environments in Cambridge, Massachusetts. In this role, you will create and deploy vision models that interpret live camera feeds to support defect detection and workflow monitoring across industrial settings. This position is ideal for an engineer who enjoys turning machine learning concepts into reliable production systems and collaborating closely with technical teams to deliver measurable operational value.<br><br>Responsibilities:<br>• Design, train, and refine computer vision models for manufacturing use cases such as defect identification, anomaly detection, and step-by-step task tracking.<br>• Build production-ready Python-based machine learning pipelines using frameworks such as PyTorch or TensorFlow.<br>• Work with image and video data captured from facility cameras to develop accurate and scalable real-time analysis solutions.<br>• Deploy and support vision applications in cloud and edge environments, including AWS services such as S3 and EC2.<br>• Collaborate with engineering leadership and cross-functional teammates to translate customer needs into practical model and system designs.<br>• Create solutions from the ground up using supervised and unsupervised learning techniques where appropriate.<br>• Improve system performance through testing, evaluation, and iterative tuning of algorithms in live operational settings.<br>• Participate in periodic onsite visits to customer facilities to understand workflows, validate model behavior, and support implementation.
We are looking for an experienced AI Manager to lead the delivery of enterprise AI applications in Houston, Texas. This role combines technical leadership with hands-on engineering, guiding full-stack AI solutions from data pipelines and backend services to user-facing applications powered by machine learning and generative AI. The successful candidate will work closely with cross-functional partners while building a strong engineering culture centered on quality, accountability, and practical innovation.<br><br>Responsibilities:<br>• Lead and develop a team of full-stack AI engineers supporting multiple projects at the same time, providing direction, mentorship, and consistent performance feedback.<br>• Contribute directly to active engineering work by helping design, build, and refine AI-enabled applications across frontend, backend, and data environments.<br>• Architect scalable solutions that connect data ingestion, application services, machine learning capabilities, and user interfaces into cohesive products.<br>• Establish and uphold engineering practices related to code reliability, testing discipline, security controls, and technical documentation.<br>• Review architecture decisions and software deliverables to maintain a high standard for performance, maintainability, and production readiness.<br>• Partner with product leaders, data engineers, and AI specialists to translate business goals into practical technical plans and delivered solutions.<br>• Promote responsible use of AI-assisted development tools and define working standards that improve code quality and team effectiveness.<br>• Assess emerging AI engineering tools and methodologies, sharing recommendations and embedding useful practices across the team.<br>• Support hiring, coaching, and team development efforts to strengthen capability, accountability, and delivery excellence.
<p>We are seeking an AI Engineer to design, develop, and deploy AI-powered applications that solve real business challenges. This role will work closely with software engineering, data, and business teams to build scalable solutions leveraging Generative AI, Large Language Models (LLMs), machine learning, and cloud platforms.</p><p>Responsibilities</p><ul><li>Design and develop AI-powered applications and services.</li><li>Build and optimize prompts, RAG pipelines, and AI workflows.</li><li>Integrate OpenAI, Azure OpenAI, and other LLM platforms into enterprise applications.</li><li>Develop APIs and microservices that support AI solutions.</li><li>Collaborate with data engineers and software developers to deploy AI models into production.</li><li>Monitor model performance and improve accuracy, reliability, and scalability.</li><li>Implement AI security, governance, and responsible AI practices.</li><li>Document technical designs and best practices.</li></ul><p><br></p>
<ul><li>Design, develop, test, and deploy AI-powered applications and services.</li><li>Build and optimize LLM and generative AI solutions using Azure OpenAI and related platforms.</li><li>Develop RAG architectures that connect LLMs to enterprise documents, databases, APIs, and other data sources.</li><li>Design and implement vector search, embeddings, semantic search, and knowledge retrieval capabilities.</li><li>Develop AI workflows using frameworks such as Semantic Kernel, LangChain, LangGraph, or Microsoft Copilot Studio.</li><li>Integrate AI solutions with existing enterprise applications, APIs, databases, and data platforms.</li><li>Develop production-quality services using Python and/or .NET/C#.</li><li>Work with Azure services including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure Storage, and related cloud services.</li><li>Build data pipelines and preprocessing workflows to prepare enterprise information for AI applications.</li><li>Evaluate LLM performance, accuracy, relevance, latency, and cost.</li><li>Implement techniques such as prompt engineering, grounding, retrieval optimization, evaluation, and guardrails.</li><li>Partner with data engineers, software engineers, architects, and business stakeholders to move AI initiatives from proof-of-concept to production.</li><li>Establish appropriate practices for security, responsible AI, data privacy, and governance.</li><li>Troubleshoot and optimize AI applications in production environments.</li><li>Stay current with emerging AI technologies, models, frameworks, and development practices.</li></ul><p><br></p>
AI/LLM Engineer / Solutions Architect - no 3rd parties, no C2C - no must be eligible to work in the U.S. - Remote with 2 weeks onsite to onboard We are looking for an Artificial Intelligence (AI) Engineer to lead practical AI development efforts for a manufacturing organization in Lincolnton, North Carolina. This Long-term Contract position will focus on creating production-ready automation tools and intelligent workflows that improve decision-making, streamline operations, and uncover business insights from enterprise data. The role is best suited for someone who can translate complex operational needs into scalable AI solutions while partnering closely with cross-functional teams such as Finance and Sales. <br> Responsibilities: • Design and deploy AI-powered applications that automate recurring operational activities and improve workflow efficiency across the business. • Build intelligent solutions that analyze enterprise and operational data to identify trends, risks, and opportunities that support growth and performance. • Create tools that provide visibility into customer purchasing behavior, inventory conditions, material planning, and seasonal business patterns. • Develop AI-driven capabilities that help teams investigate operational issues, uncover contributing factors, and support faster resolution. • Integrate AI models and services with existing business platforms, data sources, and external systems through APIs and structured pipelines. • Partner with stakeholders in Finance, Sales, and other functional areas to define use cases, prioritize deliverables, and align solutions with business goals. • Establish practical standards for AI implementation, including solution scope, governance, and responsible deployment practices. • Produce market intelligence solutions that monitor external signals such as public-sector funding activity, bid opportunities, and competitor developments. • Participate in early onsite collaboration to understand the manufacturing environment, team workflows, and operational priorities before broader delivery begins.
We are looking for an Artificial Intelligence (AI) Engineer to create and scale advanced generative AI solutions for a highly regulated financial services setting in Jacksonville, Florida. This position is ideal for a hands-on engineer who can turn concepts into dependable production applications while balancing speed, quality, and security. You will work across AI architecture, application development, and cloud deployment to deliver intelligent capabilities that support enterprise business goals.<br><br>Responsibilities:<br>• Design and implement generative AI applications and agent-based workflows that solve complex business challenges in a financial services environment.<br>• Build end-to-end AI capabilities, including solution design, development, testing, deployment, and ongoing performance monitoring.<br>• Connect large language models to enterprise products and operational processes to deliver practical, production-ready functionality.<br>• Develop and maintain data preparation workflows such as document chunking, embedding generation, indexing, and vector search optimization.<br>• Configure and manage cloud infrastructure using Terraform to support scalable, resilient, and secure AI services.<br>• Engineer robust backend components and enterprise applications using C# and the Microsoft technology stack.<br>• Collaborate with technical and business stakeholders to define requirements, prioritize deliverables, and drive high-quality execution.<br>• Ensure AI systems meet expectations for reliability, governance, data protection, and compliance within a regulated industry.<br>• Continuously refine models, pipelines, and application performance to improve accuracy, efficiency, and operational stability.
<p><strong>Software Engineer, AI</strong></p><p><br></p><p><strong>Company Overview</strong> </p><p>A growing organization is seeking an AI Engineer to develop automation, data, and AI-driven solutions that improve business processes and operational efficiency. This role offers the opportunity to work on innovative projects while helping shape the organization's use of emerging technologies.</p><p><br></p><p><strong>Role Summary</strong> </p><p>The AI Engineer will design, build, and support AI-powered applications, automation solutions, and data-driven workflows. The ideal candidate combines strong software engineering skills with experience delivering practical AI solutions in a business environment.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, and support AI-enabled applications and automation solutions.</li><li>Partner with business and technical teams to identify opportunities for process improvement.</li><li>Build integrations between AI solutions, data sources, and business applications.</li><li>Monitor solution performance and continuously improve reliability and effectiveness.</li><li>Develop and maintain technical documentation and best practices.</li><li>Support the evaluation and adoption of emerging AI technologies.</li></ul>
We are looking for a senior Azure Foundry Engineer to lead the design and implementation of enterprise AI capabilities in Fort Lauderdale, Florida. This Long-term Contract position will focus on building a strong Azure AI Foundry foundation, enabling scalable generative AI solutions, and providing architectural guidance once the environment is established. The ideal candidate brings deep experience across the Microsoft AI ecosystem and can translate complex technical needs into secure, production-ready solutions.<br><br>Responsibilities:<br>• Architect and establish an Azure AI Foundry environment within the appropriate Microsoft tenant to support enterprise AI initiatives.<br>• Create, deploy, and refine generative AI applications using Azure AI services and large language model capabilities.<br>• Connect AI solutions with Azure-based platforms, external APIs, and internal business systems to enable practical use cases.<br>• Design retrieval-based AI patterns by implementing vector storage, knowledge access strategies, and prompt workflows.<br>• Define and enforce safeguards for security, governance, observability, and responsible AI operations across deployed workloads.<br>• Improve solution efficiency by tuning performance, controlling operational costs, and planning for future scale.<br>• Provide technical direction and a clear architectural overview after the foundational environment is implemented.<br>• Collaborate with stakeholders to translate business objectives into production-ready AI engineering solutions.
<p><strong>Software Automation Engineer IV</strong></p><p><strong>Location: </strong>Remote, East Coast hours</p><p><br></p><p>We are seeking a senior-level <strong>Automation Engineer IV</strong> to help accelerate the development, deployment, and adoption of AI-enabled solutions across the enterprise. This role will sit at the intersection of <strong>Python engineering, automation, machine learning, software quality, and AI enablement</strong>, helping move AI and ML use cases from development and experimentation into reliable, scalable production environments.</p><p><br></p><p><strong><u>Responsibilities:</u></strong></p><ul><li>Help operationalize <strong>AI and machine learning solutions</strong>, moving models and AI-enabled applications from development into scalable production environments.</li><li>Develop reusable frameworks, utilities, and automation that make it easier for application teams to <strong>integrate and deploy AI capabilities</strong>.</li><li>Build Python-based services, scripts, APIs, and automation workflows supporting AI and ML use cases.</li><li>Partner with technical teams to identify opportunities where <strong>AI can improve existing applications, processes, testing, and operational workflows</strong>.</li><li>Establish repeatable development, testing, deployment, and monitoring practices for AI-enabled applications.</li><li>Code, test, document, implement, and support new or modified machine learning systems supporting a broad range of clinical and enterprise use cases.</li><li>Evaluate emerging technologies and recommend opportunities to reuse existing capabilities versus building new solutions.</li><li>Partner with various SOC Leaders, technical owners, and stakeholders to understand operational challenges and automation opportunities.</li></ul><p>Design, build, and deploy AI-powered solutions such as:</p><ul><li>AI triage bots</li><li>Watchlist automation</li><li>Incident response automation</li><li>Security operations workflows</li><li>AI agents and intelligent automation tools</li><li>Build solutions end-to-end, from requirements gathering through deployment and support.</li><li>Participate in architectural design and technical decision-making.</li><li>Integrate AI and automation tools into existing enterprise systems and workflows.</li><li>Improve SOC efficiency by reducing false positives, manual effort, and administrative tasks.</li><li>Develop software solutions utilizing AWS services and APIs.</li><li>Collaborate across security, engineering, and operations teams.</li></ul>
<p>We are looking for a Data Engineer to build and enhance reporting and data solutions that help teams make informed business decisions across the organization. This role partners with groups such as asset management, acquisitions, accounting, and HR to translate business needs into scalable dashboards, reliable data pipelines, and actionable insights. Based in Los Angeles, California, the position is ideal for someone who combines strong technical depth with the ability to explain findings clearly to a range of stakeholders.</p><p><br></p><p>Responsibilities:</p><p>• Create and refine dashboards, reports, and automated data outputs using tools such as Python, Excel, and Power BI to support operational and strategic reporting needs.</p><p>• Examine large and varied datasets to uncover meaningful trends, performance indicators, and opportunities for improvement.</p><p>• Guide and support entry-level BI team members by reviewing work, sharing best practices, and contributing to their career growth.</p><p>• Partner with stakeholders across multiple business functions to define reporting goals, gather technical requirements, and deliver effective data solutions.</p><p>• Translate technical concepts and analytical results into clear recommendations for non-technical audiences.</p><p>• Contribute to cross-department initiatives that improve data availability, reporting consistency, and overall usability of business information.</p><p>• Develop and maintain queries, procedures, and data workflows to support extraction, transformation, and loading activities across reporting environments.</p><p>• Monitor data quality through validation checks, issue resolution, and routine audits to maintain accuracy and reliability.</p><p>• Administer BI platforms with attention to performance, access control, and system stability while assisting users with adoption and training.</p><p><br></p><p>For immediate consideration, apply now and direct message Reid Gormly on LinkedIn</p>
We are looking for an AI Consultant to join a contract opportunity in New Jersey. This role is ideal for a technically strong educator and advisor who can translate advanced AI concepts into practical learning experiences for engineers, professionals, and business teams. The position combines hands-on instruction, curriculum development, and learner coaching while keeping training programs aligned with current industry applications and emerging digital technologies.<br><br>Responsibilities:<br>• Lead live training sessions covering artificial intelligence, machine learning, generative AI, data science, cloud technologies, cybersecurity, and related technical domains.<br>• Build and facilitate practical labs, workshops, and applied exercises that help learners use modern tools and frameworks in realistic scenarios.<br>• Guide participants through assignments, projects, and capstone work by offering technical mentorship, feedback, and problem-solving support.<br>• Develop and refine instructional materials, lab content, assessments, and program modules to keep learning paths current and effective.<br>• Tailor delivery methods to suit different audience backgrounds, experience levels, and business needs.<br>• Incorporate relevant industry examples, use cases, and market-informed perspectives into training sessions to strengthen real-world application.<br>• Monitor learner performance, review submissions, and provide structured evaluations that support strong completion rates and measurable outcomes.<br>• Partner with internal stakeholders to shape learning programs that reflect evolving client expectations and technology trends.
We are looking for an experienced Senior AI Product Owner to lead the planning and delivery of enterprise generative AI solutions for teams across the organization. This Long-term Contract position is based in Cedar Rapids, Iowa, and offers the opportunity to work closely with technical and business leaders to turn strategic goals into practical, scalable AI products. The role requires strong product ownership skills, comfort with complex technical discussions, and the ability to guide delivery while balancing governance, risk, and business value.<br><br>Responsibilities:<br>• Lead the full lifecycle of AI initiatives, from early discovery and use case evaluation through deployment and post-release support.<br>• Convert business priorities into well-defined epics, features, user stories, and acceptance criteria that enable efficient execution by delivery teams.<br>• Collaborate with engineers, architects, and external partners to shape solution approaches and strengthen technical design decisions.<br>• Maintain and prioritize the product backlog by weighing business impact, implementation effort, dependencies, and potential risk.<br>• Facilitate agile delivery activities such as sprint planning, reviews, demonstrations, defect management, and readiness for production release.<br>• Contribute to architecture and design conversations by assessing when generative AI is the right fit compared with other automation or machine learning approaches.<br>• Work closely with legal, compliance, security, risk, architecture, and data governance partners to support reviews, approvals, and audit-related needs.<br>• Lead discussions with executives, subject matter experts, and cross-functional stakeholders to build alignment, communicate tradeoffs, and drive informed decisions.<br>• Establish success measures and key performance indicators for AI products, track realized value, and identify opportunities to reuse capabilities across multiple use cases.
<p><strong>Software Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading artificial intelligence and advanced analytics organization is seeking an Software Engineer to help develop next-generation AI orchestration and decision-support platforms. Based in Los Angeles, California, the company specializes in integrating complex data sources into scalable intelligence solutions that support mission-critical operations, advanced analytics, and organizational workflows. This is an opportunity to work on cutting-edge AI technologies within a highly collaborative and innovative engineering environment.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Software Engineer will design, build, and optimize enterprise-grade AI platforms that connect structured and unstructured data, knowledge graphs, retrieval systems, and intelligent workflows. This hands-on role focuses on developing production-ready AI applications, agent frameworks, workflow orchestration systems, retrieval pipelines, and model-serving infrastructure. The ideal candidate combines strong software engineering fundamentals with expertise in AI systems, distributed architectures, and scalable platform development.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design and implement intelligent workflow systems for research, analysis, automation, and decision-support use cases.</li><li>Develop scalable retrieval, search, and knowledge management capabilities across structured and unstructured datasets.</li><li>Build backend services, APIs, and platform capabilities supporting AI-driven applications.</li><li>Create resilient workflow orchestration patterns for long-running, distributed, and fault-tolerant processes.</li><li>Develop authorization, permission management, auditing, and governance mechanisms within AI platforms.</li><li>Optimize retrieval, inference, and execution performance across diverse deployment environments.</li><li>Fine-tune, evaluate, and integrate open-source AI models to support specialized business workflows.</li><li>Implement model routing, inference optimization, caching, and fallback strategies.</li><li>Build evaluation frameworks that measure system accuracy, reliability, performance, and operational effectiveness.</li><li>Develop observability, monitoring, alerting, and troubleshooting capabilities across platform components.</li><li>Partner with product, data, machine learning, infrastructure, security, and customer-facing teams to deliver scalable solutions.</li><li>Contribute to technical architecture, engineering standards, and long-term platform strategy.</li></ul><p><strong>Additional Details</strong></p><ul><li>Fully onsite 5 days per week</li><li>Individual contributor role with substantial technical ownership</li><li>Opportunity to work on advanced AI, automation, retrieval, and knowledge graph technologies</li><li>Staff-level candidates may provide technical leadership, mentorship, and architecture guidance</li><li>Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements</li></ul>
We are looking for a Senior Data Engineer to develop and optimize enterprise data systems that support analytics and digital solutions. In this role, you will design and implement robust data architectures, ensuring seamless data integration and transformation processes across the organization. Your expertise will drive the creation of reliable pipelines and scalable infrastructure, enabling advanced analytics and machine learning capabilities.<br><br>Responsibilities:<br>• Design and implement scalable data pipelines using Databricks, Spark, and Delta Lake to support enterprise-level analytics.<br>• Develop and maintain efficient data models tailored for AI, analytics, and operational systems.<br>• Lead Master Data Management initiatives to establish unified and accurate data records across platforms.<br>• Create batch and near-real-time data processing workflows for structured and semi-structured datasets.<br>• Collaborate with AI and software development teams to ensure delivery of high-quality datasets for machine learning.<br>• Define and enforce data architecture standards, ensuring scalability, reliability, and governance.<br>• Troubleshoot and optimize data systems to maintain performance and reliability in complex environments.<br>• Partner with cloud and IT teams to integrate modern data platforms and ensure seamless functionality.
We are looking for an experienced Lead Data Engineer to oversee the design, implementation, and management of advanced data infrastructure in Houston, Texas. This role requires expertise in architecting scalable solutions, optimizing data pipelines, and ensuring data quality to support analytics, machine learning, and real-time processing. The ideal candidate will have a deep understanding of Lakehouse architecture and Medallion design principles to deliver robust and governed data solutions.<br><br>Responsibilities:<br>• Develop and implement scalable data pipelines to ingest, process, and store large datasets using tools such as Apache Spark, Hadoop, and Kafka.<br>• Utilize cloud platforms like AWS or Azure to manage data storage and processing, leveraging services such as S3, Lambda, and Azure Data Lake.<br>• Design and operationalize data architecture following Medallion patterns to ensure data usability and quality across Bronze, Silver, and Gold layers.<br>• Build and optimize data models and storage solutions, including Databricks Lakehouses, to support analytical and operational needs.<br>• Automate data workflows using tools like Apache Airflow and Fivetran to streamline integration and improve efficiency.<br>• Lead initiatives to establish best practices in data management, facilitating knowledge sharing and collaboration across technical and business teams.<br>• Collaborate with data scientists to provide infrastructure and tools for complex analytical models, using programming languages like Python or R.<br>• Implement and enforce data governance policies, including encryption, masking, and access controls, within cloud environments.<br>• Monitor and troubleshoot data pipelines for performance issues, applying tuning techniques to enhance throughput and reliability.<br>• Stay updated with emerging technologies in data engineering and advocate for improvements to the organization's data systems.
<p>Robert Half is working with a client in Lawrenceville, GA looking for an AI Engineer.</p><ul><li>Partner with business stakeholders to identify opportunities where AI can improve workflows, productivity, and decision-making.</li><li>Translate business challenges into scalable AI and automation solutions.</li><li>Design, develop, and implement AI-powered tools and applications.</li><li>Evaluate emerging AI technologies and recommend practical business use cases.</li><li>Work cross-functionally with leaders across finance, operations, human resources, and other business functions.</li><li>Identify repetitive and manual processes that can be automated or enhanced through AI.</li><li>Support the development of an enterprise AI roadmap and project pipeline.</li><li>Create proof-of-concepts, prototypes, and production-ready AI solutions.</li><li>Help establish best practices, governance standards, and AI adoption strategies.</li><li>Drive successful execution from concept through implementation and user adoption.</li></ul>