Staff Machine Learning Engineer, ML Platform

What you'll do

• Drive transformative initiatives to improve how the team runs machine learning in production.
• Build and ship complex infrastructure projects from initial design through final production deployment.
• Establish the technical vision and quality standards for training, deploying, and serving models.
• Manage incident response, reliability, and cost optimization for large-scale ML systems.
• Lead cross-team initiatives by managing technical relationships with partner engineering teams.
• Improve engineering quality through code reviews, design reviews, and mentoring senior staff.
• Translate technical decisions into clear business outcomes for product and leadership stakeholders.

What we're looking for

• You must have 8+ years of experience building and operating distributed systems in production.
• You must have hands-on experience with ML workloads in production including training pipelines or model serving.
• You must be a technical leader who has owned team direction, led multi-quarter initiatives, and mentored senior engineers.
• You must possess deep working knowledge of Kubernetes and cloud infrastructure, including identity management and networking.
• You must be an effective communicator capable of building consensus through written and verbal designs.
• Experience with queueing/orchestration systems like Celery, RabbitMQ, Kafka, or Ray (preferred).
• Experience with ML platform tooling such as MLflow, feature stores, or model registries (preferred).
• Experience with Python, Ruby on Rails, MongoDB, Redis, or operating under SOX/HIPAA compliance (preferred).