Checkr
Data platform
MachineLearningEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Machine Learning Engineer at Checkr. Skills: ML Engineer, AI systems, LLMs, APIs, production software, Python, OOP, CI/CD, distributed systems, NLP, AI-assisted experience. build and ship the AI systems that power Checkr’s core products. Design with LLMs and APIs”
What You'll Achieve.
deliver meaningful outcomes
Industry & Context.
solving complex problems; Translate business problems into ML solutions; evaluate tradeoffs
Individuals are expected to work from the office 3+ days a week, A relocation stipend may be available for those willing to relocate to a Checkr hub location
What They're Looking For.
Must Have
4+ years building software professionally, at least 2 of those building ML systems that run in production, Python 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, shipped code that other engineers depend on, Comfortable with distributed systems concepts: queues, async processing, caching, horizontal scaling, Experience with NLP tasks in production: classification, extraction, entity resolution, summarization, Comfort with and enthusiasm for AI-assisted experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a signal, You can evaluate tradeoffs: fine-tune vs. prompt, hosted vs. self-deployed, classical ML vs. LLM, rule vs. model, 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 bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes
Nice to Have
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
What You'll Do.
build and ship the AI systems that power Checkr’s core products
Design with LLMs and APIs
etc. ) as building blocks in production systems
Ship production software
well-structured code with solid OOP
CI/CD is how you work
Translate business problems into ML solutions
Define API contracts with product engineers
Explain your approach clearly to non-ML partners
Evaluate and iterate fast
Build evaluation frameworks
and make data-driven decisions about model and system performance
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
How You'll Work.
Team & Collaboration
Partner with product and engineering; Define API contracts with product engineers; Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion; explain technical decisions clearly to engineers and non-engineers alike
Communication Scope
Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion; explain technical decisions clearly to engineers and non-engineers alike, without hiding behind jargon
Process & Methodology
bias for action, move with urgency, take ownership to deliver meaningful outcomes
Full Job Description
About Checkr Checkr is building the data platform to power safe and fair decisions. Checkr’s innovative technology and robust data platform help customers assess risk and ensure safety and compliance to build trusted workplaces and communities. Checkr has over 100,000 customers including Amazon, DoorDash, Netflix, Kimpton, and Anthropic. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company. About the team/role We’re hiring an ML Engineer (P2) to build and ship the AI systems that power Checkr’s core products. This role sits on the ML team inside Checkr’s Data 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. What you bring A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equiv
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