Das ist der Job
Mercury
Mercury is a fintech company that provides banking services for startups via partner banks.
Darum lohnt es sich
• Mercury's ML platform team builds the paved path from model training to production deployment, ensuring reliability and observability.
• This role focuses on the production ML lifecycle including deployment, real-time inference, and retraining.
Compensation:
• Base salary range for US employees: $166,600 - $208,300; for Canadian employees: CAD 157,400 - 196,800.
• Total rewards include base salary, equity, and benefits. The company is committed to creating a safe environment and values diversity, with a growing team focused on innovation.
Key Responsibilities:
• Build and operate the real-time inference service for risk decision engine with low latency and high availability.
• Own model deployment infrastructure including CI/CD, shadow mode, and staged rollouts.
• Build model observability and partner with Risk Data Science for production operation.
Requirements:
• 5+ years in ML engineering, backend engineering, or MLOps with production ML service experience.
• Strong Python and API framework skills, plus experience with model lifecycle tooling and observability.
• Familiarity with data layer technologies like SQL, key-value stores, and streaming pipelines.
