Senior Machine Learning Engineer

Join Checkr, a leading background check company, as a Senior Machine Learning Engineer. In this role, you will build and ship AI systems that power Checkr's core products. You will own ML services end-to-end, design and develop ML models and AI systems, and partner with product and engineering teams. This is a hands-on role that requires strong engineering skills and a passion for AI-assisted workflows.

• Concevoir, développer et expédier des modèles d'apprentissage automatique et des systèmes d'IA qui sont utilisés par les équipes d'ingénierie produit.
• Utiliser des API LLM telles qu'OpenAI et Anthropic comme éléments de base dans les systèmes de production, et décider quand appeler un LLM.
• Traduire les problèmes commerciaux en solutions d'apprentissage automatique, définir les contrats d'API avec les ingénieurs produit.

• Experience building and maintaining APIs, working with CI/CD pipelines, and shipping code that other engineers depend on
• A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience
• Ruby experience
• An A-player mindset with a strong bias for action: raises the bar, moves with urgency, stays resilient through ambiguity, and takes ownership to deliver meaningful outcomes
• 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 use AI tools such as Copilot or Claude to move faster while understanding every line they produce and identifying AI slop
• Experience with PySpark or large-scale data processing
• Strong Python fluency; ability to write clean, testable, well-structured code with solid OOP instincts
• Working knowledge of dbt, Snowflake, or modern ELT/data transformation tools
• Familiarity with compliance-sensitive domains such as fintech, legal tech, or HR tech
• Experience with MLOps platforms such as MLflow, SageMaker, or Vertex
• 6+ years building software professionally, with at least 2 of those years building ML systems that run in production
• Background in document processing, OCR, or information extraction
• Hands-on experience using LLM APIs in production systems, including prompt engineering, structured outputs, function calling, cost management, and evaluation