Senior Machine Learning Operations Engineer (Fintech)

Location: San Francisco, CA; New York, NY; Portland, OR; or remote within Canada or the United States

Salary: US employees: $166,600–$208,300 USD annually; Canadian employees: $157,400–$196,800 CAD annually

Company

Mercury is a fintech company building banking services and risk decisioning products for startups, with a focus on safe experiences for customers, administrators, and regulators.

What you will do

• Build and operate low-latency, highly available real-time inference services for fraud and financial-crime risk decisions.
• Own model deployment infrastructure, including registries, versioning, model CI/CD, shadow mode, and staged rollouts.
• Develop production observability for availability, latency, errors, model drift, and retraining triggers.
• Partner with Risk Data Science to move models from development into reliable production operation.
• Implement champion/challenger and canary experimentation, including explainability outputs such as SHAP attributions.
• Help shape and build a new machine learning platform team through strong product ownership.

Requirements

• 5+ years of experience in machine learning engineering, backend software engineering, MLOps, or a related field.
• Experience deploying, serving, and operating production ML services in low-latency, high-availability environments.
• Strong Python backend engineering skills with API frameworks such as FastAPI or Flask.
• Experience with model registries, model CI/CD, versioning, and staged rollout patterns including shadow, canary, and champion/challenger deployments.
• Experience building observability and alerting for production services, including latency, errors, and ideally model drift.
• Experience with SQL, low-latency key-value stores such as Redis or DynamoDB, and streaming pipelines such as Kafka, Kinesis, or Redpanda.

Nice to have

• Familiarity with Snowflake, dbt, Dagster, Airflow, or similar modern data-stack tools.
• Experience in regulated, audit-sensitive, or compliance-adjacent environments.
• Exposure to functional languages or willingness to work with Haskell, React, and TypeScript.

Culture & Benefits

• Total rewards include base salary, equity through stock options or RSUs, and benefits.
• Small and medium projects are self-organized, with opportunities to take ownership of a new platform.
• Mercury is committed to diversity, belonging, equal employment opportunity, and reasonable accommodations throughout recruitment.