Databricks Asset Bundles Developer Jobs

1 job found

1mo ago

Machine Learning Engineer

Robert Half Los Angeles, CA

Los Angeles, CA

1mo ago Closed

$200k - $260k/yr Full time Ai Ml Artificial Intelligence Azure Databricks

This position is no longer accepting applications (closed Jul 13, 2026).

Job Description

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

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