Machine Learning Engineer

Checkr • San Francisco, CA

2d • Onsite

About The Position

Checkr is seeking an ML Engineer (P2) to join their Data & ML organization within Engineering. This role focuses on building and deploying AI systems that power Checkr's core products, including document processing, charge classification, entity resolution, and in-product intelligence. The position is production-oriented, requiring end-to-end ownership of ML services from design and coding to deployment and monitoring. The ideal candidate will have experience building AI-native software and a strong understanding of engineering craft. This role involves partnering with Product Engineering, Product, and cross-functional teams, and contributing to Checkr's broader AI strategy, including the deployment of an agentic fleet and building a semantic layer. The company is looking for someone based in San Francisco with experience in fast-moving, impact-first environments.

Requirements

• A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience
• 4+ 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
• Experience building and maintaining APIs, working with CI/CD pipelines, and shipping 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 workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a strong signal
• Ability to evaluate tradeoffs: fine-tune vs. prompt, hosted vs. self-deployed, classical ML vs. LLM, rule vs. model
• Strong communication skills; you explain technical decisions clearly to engineers and non-engineers alike, without hiding behind jargon
• 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.

Nice To Haves

• 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

Responsibilities

• Build and deploy ML/AI services, including designing, developing, and shipping ML models and AI systems.
• Design with LLMs and APIs, using them as building blocks in production systems and evaluating tradeoffs between LLMs, fine-tuning, classical models, and rules, considering cost, latency, and quality.
• Ship production software by writing clean, well-structured code with solid OOP, proper abstractions, error handling, and tests, utilizing CI/CD pipelines.
• Partner with product and engineering teams to translate business problems into ML solutions, define API contracts, and explain technical approaches clearly to non-ML partners.
• Evaluate and iterate fast by building evaluation frameworks, running experiments, and making data-driven decisions about model and system performance.
• Ship AI-powered workflows by automating pipelines, building agentic workflows, and contributing reusable skills and context to Checkr’s agentic platform.

Benefits

• Learning and development allowance
• Competitive cash and equity compensation and opportunity for advancement
• 100% medical, dental, and vision coverage
• Up to $25K reimbursement for fertility, adoption, and parental planning services
• Flexible PTO policy
• Monthly wellness stipend
• In-office perks such as lunch five times a week, a commuter stipend, and an abundance of snacks and beverages.
• A 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: Mid Level