Senior Machine Learning Operations Engineer

📋 Description

• Build and operate the real-time inference service that scores models for the risk decision engine
• Own model deployment infrastructure: registry and versioning, CI/CD with performance, bias, and
• Build model observability: availability, latency, and error monitoring, plus drift detection as a
• Partner with Risk Data Science to take models from a clean development-to-production handoff
• Implement experimentation capabilities such as champion/challenger and canary routing, and
• Feel a strong sense of product ownership and actively seek responsibility, helping to shape and

🎯 Requirements

• 5+ years in machine learning engineering, backend software engineering, MLOps, or related field
• Production ML service experience: deploying, serving, and operating models in low-latency
• Strong backend engineering fundamentals in Python, with API frameworks like FastAPI or Flask
• Experience with model deployment and lifecycle tooling: model registries, CI/CD for models
• Experience building observability and alerting for production services (latency, model-specific
• Knowledge of data layer: SQL, key-value/low-latency stores (Redis, DynamoDB, or equivalent), and

🎁 Benefits

• Competitive base salary plus equity within the SaaS and fintech industry
• Equity rewards via stock options or RSUs
• Comprehensive benefit offerings, including employer-sponsored retirement plans, healthcare, dental
• Flexible paid time off (PTO) and sick leave to support health and well-being
• Remote work or hybrid opportunities with options to work from offices in select locations