Senior ML Production Engineer – AI Services

The Briefed; Denver (CO); On-site; USD 176,000 - 244,000; Full time

Benefits offered by this job

Catered lunches (in office)

Commuter stipend

Relocation allowances

Stocked office snacks

Learning & development allowance

Job summary

Checkr’s Data & ML team is hiring a Machine Learning Engineer (P3) to build production AI systems powering verification products. You will own end-to-end ML microservices, Python API layers, monitoring, and deployment via CI/CD.

You’ll work with LLMs (OpenAI, Anthropic) and traditional ML to deliver low-latency features. The role requires 6+ years in software engineering with at least 2+ years deploying ML/AI in production, plus strong Python and OOP skills.

Qualifications

• Bachelor’s or Master’s degree in CS, Mathematics, or related field.
• 6+ years of software engineering experience with 2+ years deploying ML/AI systems.
• Strong Python fluency and OOP.
• Hands-on experience with production LLM APIs (OpenAI/Anthropic).
• Experience building REST/gRPC APIs and CI/CD pipelines.
• Familiarity with AI coding tools (Copilot, Claude, Cursor).
• Bias for action, shipping, and measurable outcomes over theory.

Responsibilities

• Design, code, test, deploy, and monitor production ML microservices.
• Integrate LLM APIs with production pipelines and evaluate trade-offs.
• Write clean, modular code and manage deployments via CI/CD workflows.
• Build agentic workflows and reusable context skills on Checkr’s platform.
• Collaborate cross-functionally with Product Eng, PMs, and Data teams.

Skills

Python

OOP

LLM APIs

REST APIs

CI/CD

AI coding tools

Execution mindset

Team collaboration

Education

Bachelors or Masters in CS/Math/related field

Tools

MLflow

AWS SageMaker

Vertex AI

PySpark

Ruby on Rails

Job description

Checkr’s Data & ML team is hiring a Machine Learning Engineer (P3) to build production AI systems powering verification products. You will own end-to-end ML microservices, Python API layers, monitoring, and deployment via CI/CD.

You’ll work with LLMs (OpenAI, Anthropic) and traditional ML to deliver low-latency features. The role requires 6+ years in software engineering with at least 2+ years deploying ML/AI in production, plus strong Python and OOP skills.