Checkr Senior Machine Learning Engineer at Checkr builds and ships production ML/AI services powering core products. The role involves designing with LLMs and APIs, writing production-quality code, and partnering with product and engineering teams.
Responsibilities
Build and deploy ML/AI services. Design, develop, and ship ML models and AI systems that Product Engineering teams rely on. You write the model code, the API layer, the monitoring, and the tests. Not notebooks; production services.
Design with LLMs and APIs. Use LLM APIs (OpenAI, Anthropic, etc.) as building blocks in production systems. You know when to call an LLM, when to fine-tune, when to use a classical model, and when to write a rule. You think about cost, latency, and quality together.
Ship production software. Write clean, well-structured code with solid OOP, proper abstractions, error handling, and tests. Your code gets reviewed by SWEs and passes. CI/CD is how you work, not something you bolt on at the end.
Partner with product and engineering. Translate business problems into ML solutions. Define API contracts with product engineers. Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion.
Evaluate and iterate fast. Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance. Ship and iterate; don’t wait for perfect.
Ship AI-powered workflows. Put AI to work on your own processes: automate pipelines, build agentic workflows, and contribute reusable skills and context to Checkr’s agentic platform. The expectation is that our teams operate AI-first.
A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience
6+ years building software professionally, with at least 2 of those building ML systems that run in production
Strong Python fluency; you write clean, testable, well-structured code with solid OOP instincts. Hands-on experience using LLM APIs in production systems: prompt engineering, structured outputs, function calling, cost management, and evaluation
You’ve built and maintained APIs, worked with CI/CD pipelines, and shipped 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 is a strong signal
You use AI tools (Copilot, Claude, etc.) to move faster, but you understand every line they produce. You can spot AI slop and you don’t ship it
Qualification
Experience with MLOps platforms (MLflowBackground in document processingWorking knowledge of dbtPay Transparency Disclosure
Preferred
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
Pay Transparency Disclosure
We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website.
