# Senior Engineering Manager, Machine Learning

**Company:** [Checkr](https://hotfix.jobs/companies/checkr)
**Location:** San Francisco, CA
**Role:** Engineering Management
**Salary:** $268k – $315k/yr
**Experience:** 10+ years
**Skills:** Machine Learning, Python, AWS, Amazon Sagemaker, Snowflake, Spark, LLMs, NLP, MLOps, CI/CD, Observability, Agent Orchestration, Entity Resolution, Ocr, Fraud Detection
**Posted:** 2026-09-08

> Leads the Machine Learning Engineering team, setting technical strategy, developing engineers, and shipping reliable ML and agentic AI systems for product intelligence, fraud detection, and workforce integrity. Requires 10+ years building production software and ML/AI systems plus substantial engineering management experience.

## Job Description

## Responsibilities
- Lead and grow the Machine Learning Engineering team by hiring, coaching, developing engineers, and building technical leadership.
- Set a focused, multi-quarter ML strategy and roadmap tied to customer outcomes, revenue, accuracy, reliability, and cost.
- Establish production engineering standards for models and agents, including APIs, testing, CI/CD, observability, on-call ownership, and reliability targets.
- Develop operating practices for evaluation, golden sets, training-data provenance, model and prompt versioning, monitoring, retraining, latency, and cost.
- Guide product intelligence systems for classification, information extraction, entity resolution, profile integrity, and measurable production accuracy.
- Launch AI and fraud products using identity, resume, device, and employment signals.
- Lead the design of agentic AI systems combining specialized models, LLMs, tools, and governed knowledge.
- Partner with Product, Engineering, Operations, Legal, Security, go-to-market teams, and company leadership.
- Communicate technical decisions and risks clearly to senior stakeholders and drive cross-functional decisions.

## Requirements
- 10+ years building software and machine learning or AI systems, with increasing scope and impact.
- 3+ years managing ML or software engineers, including hiring and developing senior and staff-level technical leaders.
- Strong software engineering foundation and experience shipping production ML systems.
- Technical depth across data and labeling, experimentation, model selection, deployment, APIs, CI/CD, observability, evaluation, retraining, and incident response.
- Experience across classical ML, deep learning, LLMs, rules, and conventional software.
- Experience setting direction for NLP, classification, extraction, entity resolution, risk, fraud, recommendation, or similar applied-ML domains.
- Experience with modern LLM systems, including structured outputs, tool use, agent orchestration, retrieval, evaluation, latency, quality, and cost trade-offs.
- Ability to translate ambiguous business problems into roadmaps, measurable outcomes, and shipped systems.
- Strong people leadership, delegation, feedback, coaching, and cross-functional influence.
- Executive-level communication and sound technical judgment.

## Nice to Have
- Experience building ML infrastructure or MLOps platforms used by multiple teams.
- Experience with document intelligence, OCR, graph systems, identity resolution, trust and safety, fraud, or risk.
- Experience operating ML in compliance-sensitive domains such as fintech, legal technology, HR technology, healthcare, or security.
- Python, AWS, SageMaker, Snowflake, Spark, and modern data tooling.
- Experience launching an AI product from customer discovery through production scale.

## Compensation and Benefits
- On-target earnings or base salary range: $268,000–$315,000 USD.
- Competitive cash and equity compensation.
- Learning and development allowance.
- Medical, dental, and vision coverage.
- Up to $25,000 reimbursement for fertility, adoption, and parental planning services.
- Flexible paid time off.
- Monthly wellness stipend.
- In-office perks, including meals, commuter stipend, and snacks and beverages.

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