Machine Learning Engineer

Robert Half is seeking a Machine Learning Engineer in Los Angeles, CA on site, with a salary range of USD 200,000 - 260,000 per year.

Responsibilities

• Architect and sustain scalable ML infrastructure on Databricks, covering experiment tracking with MLflow, a central model registry, and serving endpoints.
• Guide the ML Ops platform development and automated pipelines to deploy, monitor, and manage models in production.
• Implement robust model versioning, systematic retraining, and artifact management using Databricks Unity Catalog for ML governance.
• Design and operate the Databricks Feature Store to ensure consistent feature engineering across training and inference stages.
• Architect Retrieval-Augmented Generation (RAG) systems for document Q&A to enable business teams to query fund documents, investor letters, and market research.
• Deploy and manage vector database solutions (Databricks Vector Search, Pinecone, or similar) for semantic search across enterprise documents.
• Lead LLM fine-tuning and customization using Claude or open-source models with CIM proprietary data while upholding privacy and compliance.
• Develop and optimize document processing pipelines including PDF parsing, chunking approaches, and embedding generation for RAG applications.
• Apply prompt engineering best practices and establish LLM evaluation frameworks to ensure output quality, relevance, and factual accuracy.
• Establish guardrails for GenAI applications, including hallucination detection, output validation, and source attribution.
• Automate end-to-end ML workflows from training to deployment using Databricks Workflows and Asset Bundles.
• Set up robust CI/CD pipelines for both traditional ML models and GenAI applications using GitHub Actions, Azure DevOps, or equivalent tools.
• Automate complex data and model workflows with orchestration tools such as Airflow, Prefect, or Databricks Workflows.

Technologies

• Databricks platform stack including MLflow, Unity Catalog, Feature Store, and Vector Search
• Pinecone for vector-based retrieval
• Claude and open-source LLM options
• CI/CD tooling: GitHub Actions, Azure DevOps
• Orchestration and workflows: Airflow, Prefect, Databricks Workflows
• Asset Bundles for packaging ML assets
• Python and TensorFlow

Benefits

• Medical insurance
• Vision insurance
• Dental insurance
• Life insurance
• Disability insurance
• 401(k) plan
• Free online training