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Checkr is a data platform powering safe and fair decisions through AI verification. The company serves over 140,000 customers including Uber, Airbnb, DoorDash, and Anthropic, processing millions of background checks annually. Checkr is on the Forbes Cloud 100 2025 list and recognized as a Y Combinator 2024 Breakthrough Company.
You will join the ML team within the Data & ML organization to build and ship production AI systems that power Checkr's core products. The ML team develops systems for document processing, charge classification, entity resolution, and in-product intelligence—production services that Product Engineering teams depend on daily.
This is a hands-on engineering role, not research or notebook work. You will own ML services end-to-end: design, code, deploy, and monitor them. You'll build with LLMs and APIs as first-class tools, write production software with solid engineering practices, and distinguish between working code and AI slop.
Key responsibilities include designing and deploying ML/AI services that product teams rely on; using LLM APIs (OpenAI, Anthropic) as building blocks in production systems; writing clean, well-structured code with proper abstractions, error handling, and tests; translating business problems into ML solutions and partnering with product and engineering teams; building evaluation frameworks and iterating fast; and shipping AI-powered workflows including agentic systems.
You bring 6+ years of professional software development experience with at least 2 years building ML systems in production. You are fluent in Python, write testable and well-structured code, have hands-on experience with LLM APIs in production (prompt engineering, structured outputs, function calling, cost management, evaluation), and have built and maintained APIs with CI/CD pipelines. You are comfortable with AI-assisted workflows and use tools like Copilot or Claude to move faster while understanding every line produced. You have an A-player mindset with bias for action, urgency, and ownership.
Nice-to-have skills include experience with MLOps platforms (MLflow, SageMaker, Vertex), document processing/OCR/information extraction, and PySpark or large-scale data processing.
The role is based in San Francisco and emphasizes shipping over process, results over paperwork, and operating in fast-moving, impact-first environments.
