Senior Machine Learning Engineer

Checkr • San Francisco, CO

23h • Hybrid

About The Position

Checkr is hiring an ML Engineer (P3) for its central Data & ML team within Engineering. The role builds and operates production machine-learning and AI services that support Checkr’s background-check products, including document processing, charge classification, entity resolution, and in-product intelligence. This is an engineering role focused on shipping production services rather than research or notebook-based work. The engineer owns systems end to end, from design and implementation through deployment, testing, and monitoring, and partners with Product Engineering, Product, and other cross-functional teams. The position also contributes to Checkr’s broader AI strategy, including its agentic fleet and semantic layer. The role is based in San Francisco; Checkr expects employees to work from a hub office at least three days per week.

The engineer uses LLM APIs and other ML approaches as appropriate, balancing cost, latency, and quality. They develop clean, testable software and APIs, work with CI/CD, create evaluation frameworks, and iterate based on experiments and performance data. They are also expected to apply AI-assisted workflows to their own work and contribute reusable skills and context to Checkr’s agentic platform.

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-building 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 that other engineers depend on.
• Comfort with and enthusiasm for AI-assisted workflows.
• Ability to use AI tools while understanding their output, identifying low-quality generated code, and avoiding shipping it.
• Bias for action, ownership, urgency, resilience through ambiguity, and focus on meaningful outcomes.

Nice To Haves

• Experience with MLOps platforms such as MLflow, SageMaker, or Vertex.
• 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.
• Experience using LLMs, code-generation tools, or agentic systems in production or operational contexts.

Responsibilities

• Design, develop, and deploy production ML models and AI services used by Product Engineering teams.
• Own ML services end to end, including model code, APIs, monitoring, and tests.
• Use LLM APIs and choose appropriately among LLM calls, fine-tuning, classical models, and rules while considering cost, latency, and quality.
• Write clean, well-structured production software with appropriate abstractions, error handling, and tests; use CI/CD practices.
• Partner with Product and Engineering to translate business problems into ML solutions and define API contracts.
• Explain technical approaches clearly to non-ML partners and build cross-functional alignment.
• Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance.
• Ship and iterate on AI-powered workflows, automate processes, and contribute reusable skills and context to Checkr’s agentic platform.
• Contribute to Checkr’s broader AI strategy, including its agentic fleet and semantic layer.

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, and snacks and beverages.
• Relocation stipend may be available for those willing to relocate to a Checkr hub location.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior