Senior ML Engineer - Production AI & LLM Systems

Checkr; Denver, San Francisco (CO, CA); On-site; USD 176,000 - 207,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Fertility/adoption reimbursement

Flexible PTO

Wellness stipend

Relocation stipend

Job summary

Checkr is hiring an ML Engineer (P3) to build and ship AI-powered systems that power core products. You will own ML services end-to-end, from design to deployment, including LLMs, APIs, monitoring, and tests.

This is a production-focused role requiring strong Python, API, and CI/CD skills. Based in a Denver hub or nearby, you will collaborate with Product Engineering and cross-functional teams to drive AI-first workflows, with opportunities to shape Checkr’s agentic platform and semantic

Qualifications

• 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
• An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes.

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.

Skills

Python

LLM APIs in production

APIs in production

CI/CD pipelines

OOP fundamentals

AI workflows

Prompt engineering

Cost management

Agentic systems

Education

Bachelor’s or Master’s degree in CS/Math or equivalent

Tools

MLflow

SageMaker

Vertex

Ruby on Rails

Job description

Checkr is hiring an ML Engineer (P3) to build and ship AI-powered systems that power core products. You will own ML services end-to-end, from design to deployment, including LLMs, APIs, monitoring, and tests.

This is a production-focused role requiring strong Python, API, and CI/CD skills. Based in a Denver hub or nearby, you will collaborate with Product Engineering and cross-functional teams to drive AI-first workflows, with opportunities to shape Checkr’s agentic platform and semantic