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3 results for Rpa Engineer in Orange, CA

Infrastructure Engineer

Los Angeles, CA
onsite
Permanent / Full Time
90000 - 110000 USD / Yearly
Job TitleSystems Engineer Company OverviewA well-established organization in the media and entertainment sector, based in Los Angeles, California, is dedicated to supporting creative professionals and advancing industry standards through technology and innovation. The organization operates a highly collaborative environment where technology plays a critical role in enabling seamless operations and high-quality member services. Role SummaryThis on-site Systems Engineer role in Los Angeles, California is responsible for supporting and optimizing enterprise infrastructure across hybrid environments. Working closely with senior technology leadership, this position plays a key role in maintaining system reliability, enhancing performance, and contributing to infrastructure initiatives, including major storage and systems projects. Key Responsibilities<ul><li>Support the design, implementation, and maintenance of infrastructure systems across on-premise and cloud environments</li><li>Administer and manage Microsoft 365 and cloud-based platforms, including identity and access management systems</li><li>Maintain backup, recovery, and disaster recovery processes to ensure business continuity</li><li>Monitor system performance, security, and reliability; recommend and implement improvements</li><li>Manage and support Windows and Linux servers, virtual machines, storage systems, and network components</li><li>Troubleshoot complex technical issues across systems, endpoints, and enterprise applications</li><li>Handle escalations from technical support teams and provide guidance and mentorship when needed</li><li>Maintain documentation and resolve incidents through a structured ticketing system</li><li>Contribute to infrastructure projects, including storage system migrations and system upgrades</li><li>Participate in after-hours support as needed to maintain operational continuity</li></ul>Compensation & Benefits<ul><li>$100,000 – $110,000 + discretionary bonus</li><li>Comprehensive medical, dental, and vision coverage</li><li>401(k) with employer match</li><li>Pension program in addition to retirement savings plan</li><li>Flexible spending accounts and life insurance</li><li>Paid time off and sick leave</li><li>Long-term disability coverage</li><li>Additional employee perks and wellness offerings</li></ul>Additional Details<ul><li>Work model: 100% on-site</li><li>Standard business hours with occasional after-hours support</li><li>Hands-on role with opportunities to contribute to key infrastructure initiatives</li></ul>
2026-09-02T00:00:00Z

Machine Learning Engineer

Los Angeles, CA
onsite
Permanent / Full Time
200000 - 260000 USD / Yearly
RESPONSIBILITIES: ML Model Deployment & Platform Management • 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. • Oversee the development of the ML Ops platform and automated pipelines for deploying, monitoring, and maintaining models within production environments. • Implement robust solutions for model versioning, systematic retraining, and comprehensive artifact management using Databricks Unity Catalog for ML governance. • Design and manage Databricks Feature Store for consistent feature engineering across training and inference pipelines. Generative AI & LLM Operations • Architect and implement Retrieval-Augmented Generation (RAG) systems for document Q&A, enabling business teams to query fund documents, investor letters, and market research. • Design, deploy, and manage vector database solutions (Databricks Vector Search, Pinecone, or similar) for semantic search and retrieval across enterprise documents. • 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. • Develop and optimize document processing pipelines including PDF parsing, chunking strategies, and embedding generation for RAG applications. • Implement prompt engineering best practices and LLM evaluation frameworks to ensure output quality, relevance, and factual accuracy. • Build guardrails and safety measures for GenAI applications, including hallucination detection, output validation, and source attribution. Automation & CI/CD Pipelines • Design and implement extensive automation across the ML workflow, covering model training, testing, validation, and deployment using Databricks Workflows and Asset Bundles. • Set up robust CI/CD pipelines for both traditional ML models and GenAI applications, leveraging GitHub Actions, Azure DevOps, or similar tools. • Automate complex data and model workflows utilizing orchestration tools such as Airflow, Prefect, or Databricks Workflows.
2026-09-02T00:00:00Z

Data & ML Platform Engineer Manager

Inglewood, CA
onsite
Permanent / Full Time
180000 - 200000 USD / Yearly
Job TitleManager, Data & Machine Learning Platform Engineer Company OverviewA 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. Role SummaryThis Los Angeles-based role is a hands-on opportunity for a Manager, Data & 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. Key Responsibilities<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>Compensation & Benefits<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>Additional Details<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