Gusto

Staff Machine Learning Engineer - Risk

San Francisco, CA - Hybrid

Actively hiring, first seen by us today

Pay: $227,000–284,000/yearAnnual period assumed — pay source
Experience in the Fintech industry is a plus Our cash compensation amount for this role is targeted at $227k -284k for San Francisco. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. At Gusto, we don't use titles the traditional way, as a signal of rank or hierarchy. Instead, our titles describe two things at once — your craft (what you do, e.g. Engineering, Design) and your scope of ownership (what you're accountable for) — which is why you'll see something like "Head of X" instead of a rank word like "Director" that tells you neither. Because of this, the title on this posting may look different from what you'd expect based on the scope and seniority of the role, and from how similar roles are typically titled elsewhere. If you have questions about how this role compares to your current title or level, your recruiter can help translate.
Read the full posting
Work setting: Working pattern needs review — work setting source
Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas. 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. Reliable, consistent presence: We expect regular and predictable attendance, whether you're working in-office, hybrid, or fully remote, so that you stay closely connected to your team, customers, and stakeholders in real time and ensure colleagues and customers receive the timely support and responsiveness they deserve.
Listed location: San Francisco, CA - Hybrid
Read the full posting
Employment: Not stated

What you’ll work on

Full posting

For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the identity and risk domains.

You’ll work with an established team and seasoned leaders across Engineering, Product, Design, and Operations, spanning the Identity, Risk, and Compliance domains.

Build and deploy machine learning models to identify, assess and mitigate risks
Develop models from scratch and monitor their performance over time
Partner with Engineering, Design and Product on cross-functional risk problems
Build scalable modeling frameworks and libraries, including LLM-based data processing
Present model results and recommendations to stakeholders across the company

From the employer’s posting

For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the identity and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem.

You’ll work with an established team and seasoned leaders across Engineering, Product, Design, and Operations, spanning the Identity, Risk, and Compliance domains. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the Identity and Risk Stacks, and use ML and AI to build a world- class, high secure platform that safeguards our users’ activities and money, and ensures unparalleled reliability.

Build and deploy machine learning models to identify, assess and mitigate risks

developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model’s performance over time

Partner with Engineering, Design, and Product counterparts in Identity and Risk to solve complex cross functional problems

Develop scalable frameworks and libraries that enhance and contribute to the team’s core analysis and modeling capabilities, including through the integration of LLMs

Present and communicate results to stakeholders across the company

Education & alternatives

Here’s what we're looking for: - 8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. - Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models.

- Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion - PhD or Masters plus equivalent experience in a quantitative field is a plus - Experience in the Fintech industry is a plus

About Gusto

With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

In the employer’s words · Read in context

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Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 6, 2026today
Recorded sightings: 1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$227K–$284K against $166K–$240K, the middle half of what similar US postings state.

From 1,319 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 71.

At Gusto, jobs usually come down by about day 27.

From 4,626 similar postings that came down, and 13 of Gusto’s. Coming down is not always a hire.

Gusto is hiring

6 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring has slowed
Takes jobs down at a usual pace

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
R
XGBoost

Where the posting names them

- Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. - Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications. - Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment

- 8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. - Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. - Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications.

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

About Gusto

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy.

AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.

About the Role:

For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the identity and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem.

You’ll work with an established team and seasoned leaders across Engineering, Product, Design, and Operations, spanning the Identity, Risk, and Compliance domains. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the Identity and Risk Stacks, and use ML and AI to build a world- class, high secure platform that safeguards our users’ activities and money, and ensures unparalleled reliability.

About the Team:

Gusto’s Data Science team leverages Gusto’s rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers.

Here’s what you’ll do day-to-day:

Build and deploy machine learning models to identify, assess and mitigate risks
Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model’s performance over time
Partner with Engineering, Design, and Product counterparts in Identity and Risk to solve complex cross functional problems
Develop scalable frameworks and libraries that enhance and contribute to the team’s core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights.
Identify new opportunities to leverage data to improve Gusto’s products and help risk management team to understand business requirements and develop tailored solutions
Present and communicate results to stakeholders across the company

Here’s what we're looking for:

8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting.
Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models.
Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications.
Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment
Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion
PhD or Masters plus equivalent experience in a quantitative field is a plus
Experience in the Fintech industry is a plus

Our cash compensation amount for this role is targeted at $227k -284k for San Francisco. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

At Gusto, we don't use titles the traditional way, as a signal of rank or hierarchy. Instead, our titles describe two things at once — your craft (what you do, e.g. Engineering, Design) and your scope of ownership (what you're accountable for) — which is why you'll see something like "Head of X" instead of a rank word like "Director" that tells you neither. Because of this, the title on this posting may look different from what you'd expect based on the scope and seniority of the role, and from how similar roles are typically titled elsewhere. If you have questions about how this role compares to your current title or level, your recruiter can help translate.

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). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale.

Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas.

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.

Reliable, consistent presence: We expect regular and predictable attendance, whether you're working in-office, hybrid, or fully remote, so that you stay closely connected to your team, customers, and stakeholders in real time and ensure colleagues and customers receive the timely support and responsiveness they deserve.

Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto.

Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. 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. We want to see our candidates perform to the best of their ability. 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.

Gusto takes security and protection of your personal information very seriously. Please review our Fraudulent Activity Disclaimer.

Personal information collected and processed as part of your Gusto application will be subject to Gusto's Applicant Privacy Notice.

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