Senior ML Ops Engineer leads the design and maintenance of scalable, secure infrastructure for ML model deployment, lifecycle management, and Generative AI enablement. Responsible for building and operating the firm's ML Ops platform on Databricks, with a strategic focus on productionizing GenAI/LLM solutions including Retrieval-Augmented Generation (RAG) systems and vector database implementations.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
- 7+ years of experience as an ML Ops Engineer, ML Engineer, or similar role with production deployment responsibility.
- Expert-level proficiency in Python, complemented by strong skills in Bash scripting.
- Extensive experience designing and implementing cloud solutions on Azure (required) or GCP.
- Deep expertise with Docker and Kubernetes for containerizing and orchestrating ML workloads.
- Hands-on experience with CI/CD tools such as GitHub Actions, Jenkins, GitLab CI, or Azure DevOps.
- Strong SQL proficiency and practical experience with Databricks platform.
- Experience with workflow orchestration tools (Airflow, Prefect, or Databricks Workflows) and monitoring tools (Prometheus, Grafana, Evidently AI).
- Demonstrated experience building and deploying RAG (Retrieval-Augmented Generation) systems in production environments.
- Hands-on experience with vector databases (Databricks Vector Search, Pinecone, Weaviate, Chroma, or Milvus).
- Experience with LLM APIs and frameworks (OpenAI, Anthropic Claude, LangChain, LlamaIndex).
- Understanding of embedding models, chunking strategies, and retrieval optimization techniques.
- Knowledge of prompt engineering best practices and LLM evaluation methodologies.
Benefits
- Variety of Medical, dental, and vision benefit plans
- Health Savings Account with a generous employer contribution
- Company paid life and disability insurance
- 401(k) savings plan, with company match
- Comprehensive paid time off, including vacation days, 10 designated holidays, sick time, and bereavement leave
- Up to 16 hours of volunteer time off
- Up to 16 weeks of Paid Parental Leave
- Ongoing professional development programs
- Wellness program, including monthly and quarterly prizes
