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2 results for Rpa Engineer in Los Angeles, 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