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Salary: USD 207,000 - 244,000 / annual
Checkr is building a data platform to power safe and fair decisions. The company processes millions of background checks annually for major customers including Uber, Airbnb, DoorDash, and Anthropic. Checkr is recognized on the Forbes Cloud 100 2025 list and is a Y Combinator 2024 Breakthrough Company.
You will join the ML team within Checkr's Data & ML organization, building and shipping AI systems that power the company's core products. The ML team develops production services for document processing, charge classification, entity resolution, and in-product intelligence that Product Engineering teams depend on daily.
This is a production-focused 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, and distinguish between working code and AI slop.
Key responsibilities include:
- Design, develop, and ship ML models and AI systems that other engineering teams rely on, including model code, API layers, monitoring, and tests
- Use LLM APIs (OpenAI, Anthropic, etc.) as building blocks in production systems, making informed decisions about when to call an LLM, fine-tune, use classical models, or write rules
- Write clean, well-structured code with solid OOP, proper abstractions, error handling, and tests that pass code review
- Translate business problems into ML solutions and partner with product engineers to define API contracts
- Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance
- Contribute to Checkr's agentic platform by building agentic workflows and reusable skills
You will work in a fast-paced, impact-first environment with less process and more shipping. The role sits in the central Data & ML team and requires daily partnership with Product Engineering, Product, and cross-functional teams. You'll also contribute to Checkr's broader AI strategy, including deployment of agentic fleets and building scalable context with the semantic layer.
Checkr expects in-office work 3+ days per week from hub locations (Denver, San Francisco, Nashville, or Santiago). In-office perks include lunch five times a week, commuter stipend, and snacks/beverages. A relocation stipend may be available.
REQUIREMENTS:
- Bachelor's or Master's degree in Computer Science, Mathematics, or related technical field, or equivalent depth from experience
- 6+ years building software professionally, with at least 2 years building ML systems that run in production
- Strong Python fluency with clean, testable, well-structured code and solid OOP instincts
- Hands-on experience using LLM APIs in production systems: prompt engineering, structured outputs, function calling, cost management, and evaluation
- Experience building and maintaining APIs, working with CI/CD pipelines, and shipping code that other engineers depend on
- Comfort with and enthusiasm for AI-assisted workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts
- Ability to use AI tools (Copilot, Claude, etc.) to move faster while understanding every line they produce and spotting AI slop
- A-player mindset with strong bias for action, raising the bar, moving with urgency, staying resilient through ambiguity, and taking ownership
NICE TO HAVE:
- Experience with MLOps platforms (MLflow, SageMaker, Vertex, or similar)
- Background in document processing, OCR, or information extraction
- Experience with PySpark or large-scale data processing
- Ruby experience (Checkr's platform runs on Rails)
- Familiarity with compliance-sensitive domains (fintech, legal tech, HR tech)
- Working knowledge of dbt, Snowflake, or modern ELT/data transformation tools
