# Gusto — Head of AI and Machine Learning Engineering

- Generated: 2026-08-25 06:38:37 PM EDT
- Original/canonical posting: https://jobright.ai/jobs/info/6a10326183d7144289824957
- Jobright source: https://jobright.ai/jobs/info/6a10326183d7144289824957
- Posted: 2026-08-15 05:51:18 AM EDT
- Valid through: 2026-09-15 05:51:18 AM EDT
- Applicants: Not disclosed
- Work model/location: Remote, United States; office-based employees in Denver, San Francisco, and New York attend 2-3 days weekly
- Employment type: FULL_TIME
- Compensation: $275,000-$305,000 plus equity
- Travel: Not disclosed
- Positioning track: Executive leader
- Fit outcome: BORDERLINE — 78%

## Direct-match strengths

AI/ML strategy, production GenAI, agents, retrieval, evaluation, platform guardrails, observability, governance, executive communication, and regulated-enterprise delivery are excellent matches.

## Hard or material gaps

Material management-scope gap: the role owns a broad organization spanning ML Engineering, ML Platform, Risk Data Science, and AI Scientists. Keith has built AI teams and global technical communities, but direct ownership of this full multi-discipline organization and fintech risk-modeling function is not established.

## Evidence map

1. AI/ML systems strategy — 3/3: Direct IDW, AWS, and NorthBay leadership.
2. Production AI platform — 3/3: Direct AssistX and enterprise platforms.
3. Evaluation, observability, governance — 3/3: Direct governance and platform evidence.
4. Executive cross-functional leadership — 3/3: Direct C-suite and enterprise work.
5. Broad multi-discipline AI organization — 1/3: Adjacent teams and communities, not the stated full scope.
6. Risk modeling/fintech — 1/3: Regulated financial-services work but no direct risk-model ownership.

## Full normalized job description

Note: The job is a remote job and is open to candidates in USA. Gusto is a company dedicated to supporting the small business economy by handling essential services like payroll and HR. They are seeking a strategic Head of AI and Machine Learning Engineering to lead the development and implementation of AI/ML systems that enhance customer experiences and streamline operations.
Responsibilities
Lead, manage, and develop a broad AI/MLE organization spanning Machine Learning Engineering, ML Platform, Risk Data Science, and AI Scientists, fostering a culture of technical excellence, customer impact, collaboration, and continuous learning
Define and execute Gusto’s AI/ML systems strategy, unifying classical ML, GenAI, risk modeling, and platform capabilities into a coherent approach that supports Gusto’s broader business and product goals
Partner with senior leaders across Product, Engineering, Design, Data, Risk, Legal, Security, and business teams to identify where AI/ML can create meaningful customer value, business impact, and operational leverage
Shape how AI-native products and internal systems are built at Gusto, helping teams translate business problems into end-to-end AI/ML systems with clear standards for evaluation, monitoring, observability, reliability, safety, governance, and long-term maintainability
Lead the development and maturation of AI/ML platform capabilities, tooling, primitives, guardrails, and deployment patterns that make it easier for product and engineering teams to build, evaluate, deploy, and operate AI/ML systems with less friction, more autonomy, and the right quality bar
Drive disciplined technical and business judgment around AI/ML investments, including where to build, where to leverage existing capabilities, and where to avoid unnecessary complexity
Create room for fast experimentation and learning where appropriate, while ensuring high-impact production systems meet strong standards for quality, operational rigor, and business accountability
Set clear goals, KPIs, and operating rhythms to measure the performance, adoption, and business impact of AI/ML systems, and communicate progress and tradeoffs clearly to senior leadership
Stay close to the frontier of AI/ML advancement and help Gusto apply new technologies pragmatically, with strong judgment about what is durable, useful, and ready for production
Skills
10+ years of experience leading teams in applied machine learning, AI, engineering, or data science roles, with a track record of delivering impactful customer-facing software solutions
Deep technical expertise across AI/ML systems, including classical ML, GenAI/LLMs, statistical modeling, risk modeling, and production-scale deployment
Strong software engineering and systems background, with the ability to lead technical strategy across data, retrieval, evaluation, deployment, routing, monitoring, observability, feedback loops, and lifecycle management
Experience leading and scaling high-performing technical organizations, including Machine Learning Engineers, AI/ML Platform teams, Risk Data Scientists, and/or AI Scientists
Experience evolving ML teams toward a stronger software engineering and systems orientation, with clear ownership for building, operating, and improving production AI/ML systems
Strong platform orientation, with experience building tools, primitives, guardrails, and self-service capabilities that help product and engineering teams build AI/ML-powered products safely and effectively
Executive-level strategic judgment, with the ability to shape company-level AI/ML priorities, align senior leaders around tradeoffs, and make clear investment decisions based on customer value, business impact, technical feasibility, risk, data readiness, and operational complexity
Strong executive communication and influence, with the ability to explain complex AI/ML concepts and technical decisions in a way that clarifies strategy, tradeoffs, risk, investment needs, and organizational implications
Experience operating as a peer to senior cross-functional leaders across product, engineering, design, data, risk, legal, security, and business teams — bringing clarity, urgency, and practical judgment to ambiguous company-level opportunities
A clear thesis on how classical ML and GenAI should work together, how modern AI platform capabilities like retrieval, evaluation, agents, and observability should come together, and how AI/ML teams should evolve as the field becomes more software- and systems-oriented
Experience in fintech, risk modeling, regulated environments, or domains with high standards for reliability, trust, and compliance is a plus
Advanced degree in computer science, data science, machine learning, statistics, or a related field is a plus, but demonstrated systems leadership, production judgment, and executive-level impact matter most
Benefits
All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success.
Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately  2-3 days  per week (or more depending on role).
When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees.
Gusto is proud to be an equal opportunity employer.
Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law.
Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.
If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you.
Company Overview
Gusto is an HR and payroll platform that simplifies complex tasks, empowering businesses to focus on what matters most. It was founded in 2011, and is headquartered in San Francisco, California, USA, with a workforce of 1001-5000 employees. Its website is https://www.gusto.com.
Company H1B Sponsorship
Gusto has a track record of offering H1B sponsorships, with 13 in 2026, 49 in 2025, 54 in 2024, 19 in 2023, 37 in 2022, 24 in 2021. Please note that this does not guarantee sponsorship for this specific role.

## Artifact metadata

- Resume and cover letter: Not generated under the fit gate.
- Google Drive used: No