Software Engineer, ML Platform
Gusto
$160,000 - $200,000 / year
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Description
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:
Gusto is looking for a strong Machine Learning Platform and Infrastructure Engineer to join our ML Platform team and build out and scale our ML and AI platform.
As a Machine Learning Platform Engineer, you will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring both reliability and effectiveness. Your deep expertise in the machine learning model development cycle, along with a strong understanding of data pipelines and data infrastructure will be crucial in developing a dependable and scalable ML/AI infrastructure for all of Gusto to rely on.
The ideal candidate is passionate about developing software, developing and documenting optimal processes, working with data, and understanding the needs of end users. A strong grasp of ML and data infrastructure is essential, as you will work with stakeholders to build efficient solutions to help our partners scale x times better.
Here’s what you’ll do day-to-day:
- Build core components of our ML and AI Platform technical roadmap to design and build MLOps solutions with automated pipelines and standardized processes to build, deploy, run, monitor, debug, and retrain ML and AI Models.
- Develop, maintain, and enhance frameworks for machine learning model development and deployment.
- Collaborate with the ML/AI builders and application owners to determine business requirements and SLAs for API-enabled services.
- Develop, maintain, and enhance infrastructure supporting machine learning services.
- Support the development of new patterns for the deployment of machine learning models with CI/CD pipelines and automated testing.
- Apply AI tools as a regular part of your engineering workflow, and bring an AI-native lens to engineering and product decisions: identify where AI can reduce effort, simplify complex workflows, and surface proactive guidance.
- Adopt the latest best practices for using AI technologies across all aspects of technical development
Here’s what we're looking for:
- At least 5+ years of software engineering experience (Python, Ruby or Java).
- Demonstrated experience designing and developing infrastructure and platform services for machine learning lifecycle, such as feature stores, model development, deployment, and observability tools and solutions.
- Experience with at least one of the major cloud platforms (AWS preferred but not required).
- Curiosity and experimentation with emerging AI frameworks, applying and sharing best practices to evaluate and scale AI use safely across teams
- Comfort with AI-assisted development tools and a habit of staying current with emerging approaches to building software.
Our cash compensation amount for this role is targeted at $160,000-$200,000/year in Denver, and $190,000- $240,000/ year for San Francisco and New York. 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.
Benefits
- health insurance
- 401(k)
- stock options
About this role
Gusto's ML Platform team is building the infrastructure that enables machine learning and AI across the company's payroll and HR services for over 500,000 small businesses. This role sits at the intersection of software engineering and machine learning operations—you'll design and build the core MLOps solutions, data pipelines, and deployment frameworks that allow ML engineers to develop, test, and scale models reliably. The work spans the full ML lifecycle: automated training pipelines, model deployment with CI/CD, monitoring and debugging tools, and the infrastructure needed to keep these systems running at scale.
You'll need at least five years of software engineering experience (Python, Ruby, or Java) and demonstrated expertise building infrastructure for machine learning—whether that's feature stores, model development platforms, or observability tools. Cloud platform experience (AWS preferred) is expected, along with genuine curiosity about emerging AI frameworks and comfort using AI-assisted development tools as part of your daily workflow. The role requires someone who can translate business requirements and SLAs into technical solutions while collaborating closely with both ML engineers and application owners.
Based in Denver with hybrid flexibility (2–3 days in office weekly), this position offers $160,000–$200,000 annually, plus equity, competitive benefits, and health insurance. Gusto values people who are passionate about building software, documenting processes, and understanding end-user needs—traits that matter when you're building platforms others depend on.
How this employer is doing
solid
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Pay for this role
$160,000 to $200,000 per year
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