Manager, Machine Learning Engineering

What you'll do

• Own production ML/AI infrastructure reliability, including training pipelines, feature stores, model serving, monitoring, and incident response.
• Hire and develop an ML/AI operations team; set technical direction and establish operational standards, on-call processes, SLOs/SLAs, and postmortems.
• Partner across teams to move models into production, oversee generative AI operations, and manage platform/vendor and build-versus-buy decisions.

What they ask for

• 7+ years building and shipping production machine learning systems, including ownership of backend services and ML pipelines in a high-availability environment.
• 1-3+ years directly managing engineers, with a record of hiring and developing teams.
• Strong proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, and Scikit-learn, plus software engineering fundamentals.
• Experience operating real-time model serving at scale, building reliable data and features, and implementing production ML monitoring.

Nice to have

• Familiarity with generative AI/LLM infrastructure and operational considerations.
• Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Data Science, or a related technical field.

Pay

$219,000 - $329,000 USD base salary

Tools

Python, AWS, Databricks, Docker, Kubernetes, Terraform, Snowflake, GitHub

AI focus

Leads operations for production ML and generative AI systems, including safe, scalable deployment, monitoring, reliability, and cost management.