Senior Machine Learning Engineer
About The Position
Checkr is hiring an ML Engineer (P3) for its central Data & ML team within Engineering. The team builds production machine learning systems that make background checks faster, more accurate, and less costly, including document processing, charge classification, entity resolution, and in-product intelligence. This is an engineering role focused on owning ML services end to end—not research or notebook work—including designing, coding, deploying, testing, and monitoring production systems. The role uses LLM APIs and other approaches as production building blocks, with decisions balancing cost, latency, and quality. The engineer will partner with Product Engineering, Product, and cross-functional teams to translate business problems into ML solutions, define API contracts, and communicate technical approaches clearly. They will also contribute to Checkr’s broader AI strategy, including its agentic fleet and semantic layer, and help the organization adopt AI-first workflows. The role is based in San Francisco, with an expectation to work from a Checkr hub office at least three days per week.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience.
- At least 6 years of professional software development experience, including at least 2 years building ML systems that run in production.
- Strong Python fluency and ability to write clean, testable, well-structured code with solid object-oriented programming instincts.
- Hands-on experience using LLM APIs in production systems, including prompt engineering, structured outputs, function calling, cost management, and evaluation.
- Experience building and maintaining APIs, working with CI/CD pipelines, and shipping code other engineers depend on.
- Comfort and enthusiasm for AI-assisted workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a strong signal.
- Ability to use AI tools while understanding their output, identifying low-quality AI-generated code, and ensuring it is not shipped.
- Strong bias for action, ownership, resilience through ambiguity, urgency, and focus on delivering meaningful outcomes.
Nice To Haves
- Experience with MLOps platforms such as MLflow, SageMaker, Vertex, or similar.
- Background in document processing, OCR, or information extraction.
- Experience with PySpark or large-scale data processing.
- Ruby experience.
- Familiarity with compliance-sensitive domains such as fintech, legal tech, or HR tech.
- Working knowledge of dbt, Snowflake, or modern ELT/data transformation tools.
Responsibilities
- Design, develop, and deploy ML models and AI systems used by Product Engineering teams.
- Build and maintain production services, including model code, API layers, monitoring, and tests.
- Use LLM APIs and select among LLMs, fine-tuning, classical models, and rules based on cost, latency, and quality.
- Write clean, well-structured production code with appropriate abstractions, error handling, and tests.
- Work with CI/CD pipelines and ship code that other engineers depend on.
- Partner with product and engineering teams to translate business problems into ML solutions and define API contracts.
- Explain technical approaches clearly to non-ML partners and build alignment.
- Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance.
- Iterate quickly on shipped systems and workflows.
- Automate pipelines, build agentic workflows, and contribute reusable skills and context to Checkr’s agentic platform.
- Use AI-assisted tools while reviewing their output and ensuring code quality.
Benefits
- Learning and development allowance.
- Competitive cash and equity compensation, with opportunity for advancement.
- 100% medical, dental, and vision coverage.
- Up to $25,000 reimbursement for fertility, adoption, and parental planning services.
- Flexible PTO policy.
- Monthly wellness stipend.
- In-office lunch five times a week, commuter stipend, snacks, and beverages.
- A relocation stipend may be available for those willing to relocate to a Checkr hub location.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
