3 hours ago
Base Salary
$167k - $208k/yr
Responsibilities
- Build and operate a low-latency, highly available real-time inference service for the risk decision engine.
- Own model deployment infrastructure, including registries, versioning, model CI/CD checks, shadow mode, and staged rollouts.
- Build production and model observability for availability, latency, errors, and drift-based retraining triggers.
- Partner with Risk Data Science on development-to-production handoffs and ongoing model operation.
- Implement champion/challenger, canary routing, experimentation, and SHAP explainability outputs.
- Help shape and build a new machine learning platform team with strong product ownership.
Requirements
- 5+ years of experience in machine learning engineering, backend software engineering, MLOps, or a closely related field.
- Experience deploying, serving, and operating production ML models in low-latency and high-availability environments.
- Strong Python backend engineering fundamentals and experience 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 approaches.
- Experience building observability and alerting for production services, including latency and error monitoring and ideally model drift signals.
- Comfort with SQL, low-latency or key-value stores such as Redis and DynamoDB, and streaming pipelines such as Kafka, Kinesis, or Redpanda.
- Familiarity with Snowflake, dbt, Dagster, or Airflow is preferred.
- Experience in regulated, audit-sensitive, or compliance-adjacent environments is preferred.
- Exposure to Haskell, React, and TypeScript or willingness to work across that stack is preferred.
Benefits
- The total rewards package includes base salary, equity through stock options or RSUs, and benefits.
- The role is open to US employees in any location and Canadian employees in any location.
- Target base salary is $166,600—$208,300 USD for US employees and $157,400—$196,800 CAD for Canadian employees.
Tech Stack
Amazon DynamoDBApache AirflowApache KafkadbtFastAPIFlaskHaskellPythonReactRedisSnowflakeSQLTypeScript
Categories
About Mercury
Mercury builds a fintech platform for startups and growing businesses to run banking and financial workflows, including business accounts, payments, corporate and debit cards, bill pay, and treasury. It is a non-bank company with banking services provided by partner banks (Choice Financial Group and Column N.A.) and earns revenue from interchange and financial services fees. Founded in 2017 and headquartered in San Francisco, it is privately held.