Senior ML Back-end Engineer

The Role We are looking for a Senior Engineer to architect the backbone of our financial decisioning platform. You will not just build APIs; you will design the high-concurrency systems that serve our ML models in real-time. You will set the standards for Asynchronous Python, Database Performance, and System Observability, while mentoring junior engineers to write robust, production-grade code. Key Responsibilities: System Architecture: Design and maintain high-performance, asynchronous microservices using FastAPI. Make critical architectural decisions regarding API standards (REST vs GraphQL) and service boundaries. ML Integration: Integrate machine learning models into core backend services and business workflows. You will orchestrate how our applications consume internal model APIs (e.g., Credit Scoring, Pricing) to ensure seamless decision-making. Database & Data Modeling: Own the schema design in PostgreSQL. Optimize complex queries, manage migrations using Alembic, and ensure strict data validation standards using Pydantic. Observability Strategy: Define and implement the logging, tracing, and metrics strategy using OpenTelemetry and the Grafana Stack (Loki, Tempo, Prometheus). Ensure we have full visibility into system latency and health. Engineering Excellence: Enforce high code quality standards through code reviews. Champion Functional Programming patterns, rigorous testing (PyTest), and Clean Architecture principles. Mentorship: Act as a technical lead for the squad, guiding junior engineers in debugging, design patterns, and git workflows. Experience: 5+ years in Backend Engineering, with significant exposure to data-intensive applications or Fintech. Python Mastery: Expert-level knowledge of Python 3.10+. Deep understanding of AsyncIO, concurrency, and Functional Programming paradigms. Framework Expertise: Proven experience scaling FastAPI applications in production. Knowledge of dependency injection, middleware, and ASGI standards. Database Internals: Advanced knowledge of PostgreSQL (indexing, locking strategies, query planning) and experience with ORMs/Migration tools (SQLAlchemy/Alembic). Infrastructure & DevOps: Strong experience with Docker, CI/CD pipelines, and modern package managers (e.g., uv, Poetry). Code Quality: Strong ability to write highly optimized, clean, and maintainable code. You understand algorithmic complexity, memory management, and how to write Python that performs efficiently at scale. GenAI (Bonus): Knowledge of GenAI application development (LLMs, RAG, Vector Databases) is a strong plus. Office environment: When you come to our b_labs office, you'll find creative workspaces and an open design to foster collaboration between teams. Flexibility: You know best whether you want to work from home or in the office. Equipment: From "Day 1" you will receive all the equipment you need be successful at work.