Senior Engineering Manager, Machine Learning

About Checkr
Checkr is building the data platform to power safe and fair decisions. Over 140000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job a new place to live a car ride childcare even a date. Customers include Uber Pennymac Airbnb Doordash and Anthropic.

Were a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes CloudList and is a Y Combinator 2024 Breakthrough Company.

We are hiring a Senior Engineering Manager to lead the Machine Learning Engineering team inside Checkrs Data & ML organization. This team sits at the heart of our products strategic advantage making millions of background checks faster more accurate and more trustworthy.

The team owns three connected areas:

• Core product intelligence: NLP and classification systems entity resolution profile integrity model accuracy and the production services that power Checkrs products.
• Workforce integrity: resume and identity fraud multi-signal risk detection and new products that help customers identify sophisticated hiring fraud
• ML and agent infrastructure: evaluation systems observability model lifecycle agent orchestration and reusable infrastructure that helps every team ship reliable AI faster.

This is an engineering leadership role not a research-management role: you will lead ML engineers across seniority levels stay close enough to the work to set technical direction and hold the team accountable for production outcomes. You will decide where ML should continue to create a strategic advantage for Checkr.

You will also shape Checkrs broader AI strategy. The near-term agenda includes building a measurable accuracy moat in our core products launching an end-to-end workforce-integrity product and creating the evaluation and knowledge infrastructure required to operate AI agents in a regulated role reports to the Sr. Director of Data & ML within Engineering. This role is based in San Francisco. We are looking for someone who is seeking less process and more shipping less paperwork and more results.

What youll do

• Lead and grow the ML Engineering team. Hire coach and develop ML engineers. Set clear ownership grow technical leaders and build a team that generates its own roadmap.
• Set the strategy and roadmap. Turn ambiguous company priorities into a focused multi-quarter ML agenda. Put investment on work that improves customer outcomes revenue accuracy reliability or cost. Stop work that does not.
• Raise the production engineering bar. Models and agents ship as dependable software: clear APIs tests CI/CD observability on-call ownership and defined reliability targets.
• Build the ML operating model. Establish shared approaches to evaluation golden sets training-data provenance model and prompt versioning monitoring retraining latency and cost. Replace artisanal evaluation with repeatable systems.
• Advance core product intelligence. Guide systems for classification information extraction entity resolution profile integrity and accuracy. Make model quality measurable in production and drive the feedback loops that improve it.
• Launch new AI and fraud products. Partner with Product Security Operations and go-to-market teams to turn signals across identity resume device and employment data into customer products.
• Lead Checkrs agentic transition. Guide the design of AI systems that combine specialized models LLMs tools and governed knowledge.
• Operate as an executive partner. Explain technical choices and risks in plain language. Align Product Engineering Product Operations Legal Security and company leadership when incentives or constraints conflict.
• Model AI-native leadership. Use AI to increase the teams speed and ambition. Keep ownership of every output. As generated code becomes cheaper raise the bar on judgment verification and system design.

What you bring

• 10 years building software and machine learning or AI systems with a clear progression in scope and impact.
• 3 years managing ML or software engineers including hiring and developing senior and staff-level technical leaders.
• A strong software-engineering foundation and a record of shipping ML systems that run in production.
• Technical depth across the ML lifecycle: data and labeling experimentation model selection deployment APIs CI/CD observability evaluation retraining and incident response.
• Sound judgment across classical ML deep learning LLMs rules and conventional software.
• Experience setting direction for NLP classification extraction entity resolution risk fraud recommendation or similarly complex applied-ML domains.
• Fluency with modern LLM systems including structured outputs tool use agent orchestration retrieval evaluation latency quality and cost trade-offs.
• A record of translating an ambiguous business problem into a sharp roadmap measurable outcomes and shipped systems.
• Strong people leadership. You create leverage through clear ownership candid feedback delegation and coaching.
• Executive-level communication and cross-functional influence. You can make a hard technical trade-off legible to senior leaders and leave the room with a decision.
• You use modern AI tools to move faster verify their output and can spot plausible-looking work that should not ship.
• 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 have

• Built ML infrastructure or MLOps platforms used by multiple teams.
• Document intelligence OCR graph systems identity resolution trust and safety fraud or risk.
• Operated ML in a compliance-sensitive domain such as fintech legal tech HR tech healthcare or security.
• Python AWS/SageMaker or similar cloud ML platforms Snowflake Spark and modern data tooling.
• Launched a new AI product from early customer discovery through production scale.

#LI-TD1

What We Offer

• A fast-paced and collaborative environment
• 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

At Checkr we believe an in office work environment strengthens collaboration drives innovation and encourages connection. Our hub locations are Denver CO; San Francisco CA; Nashville TN; and Santiago Chile. Individuals are expected to work from the office 3 days a -office perks are provided 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.

Equal Employment Opportunities at Checkr
Checkr is committed to building the best product and company which requires hiring talented and qualified individuals with a diverse set of perspectives and lived experiences. Checkr believes in hiring people of all backgrounds including those whose histories are impacted by the justice system in accordance with local state and/or federal laws including the San Franciscos Fair Chance Ordinance.

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