Senior Machine Learning Operations Engineer

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Develop and manage the real-time inference service that evaluates models for the risk decision engine, prioritizing low latency and high availability.

• Take ownership of the model deployment infrastructure, including registry and versioning, CI/CD processes with performance, bias, and consistency evaluations, shadow mode, and staged rollouts.

• Establish model observability, ensuring monitoring of availability, latency, and errors, along with drift detection to trigger retraining.

• Collaborate with Risk Data Science to transition models from a seamless development-to-production handoff to operational production under MLP oversight.

• Implement experimentation features such as champion/challenger and canary routing, as well as explainability outputs like SHAP attributions.

• Exhibit a strong sense of product ownership and proactively pursue responsibilities — our team self-organizes on small to medium projects, and we seek someone eager to contribute to the creation of a new platform team.

⛳️ Requirements

• A minimum of 5 years of experience in machine learning engineering, backend software engineering, MLOps, or a related discipline.

• Proven experience with production ML services — deploying, serving, and managing models in environments requiring low latency and high availability.

• Solid backend engineering skills in Python, including familiarity with API frameworks such as FastAPI or Flask.

• Experience with model deployment and lifecycle management tools: model registries, CI/CD for models, version control, and staged rollout strategies (shadow, canary, champion/challenger).

• Background in creating observability and alerting systems for production services — focusing on latency, errors, and ideally model-specific metrics like drift.

• Proficiency with the data infrastructure essential to ML, including SQL, key-value/low-latency stores (Redis, DynamoDB, or similar), and streaming pipelines (Kafka, Kinesis, Redpanda, or equivalent).

🏝️ Benefits

• Competitive salary

• Equity

• Health insurance plans

• Paid time off

• Remote work options