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About the Role

As a Staff Software Engineer on the Machine Learning Infrastructure Team, you will be a senior technical leader responsible for setting technical direction for the AI/ML platform and the AI evaluation platform. You will design, build, and ship significant systems, partner with applied scientists and product engineering teams, and ensure the platform scales with the company's growing AI ambitions.

Responsibilities

Build and evolve core AI platform capabilities that enable teams to develop, run, and scale GenAI-powered applications.
Contribute to the design, development, and deployment of scalable tools and infrastructure for applied scientists, including traditional ML model training and serving systems, feature and data workflows, CI/CD, orchestration, deployment, and evaluation tooling.
Work hands-on across the stack, from backend services and execution infrastructure to integrations with AI models and tooling.
Partner with senior engineers to evaluate next-generation AI infrastructure frameworks and tools.
Drive projects to completion with a strong focus on business impact and measurable outcomes.
Solve complex technical problems and stay up to date with advances in this rapidly evolving space.

Requirements

10+ years of professional software engineering experience, with a track record of technical leadership at staff level or equivalent scope, setting direction for systems spanning multiple teams, driving alignment across teams, and seeing them through to production.
3+ years building AI/ML infrastructure in production including model serving, feature platforms, training or orchestration systems, or ML observability.
Hands-on experience with LLM-powered systems in production, including at least some of the following: LLM gateways or proxies, prompt and model lifecycle management, RAG or agentic architectures, and cost optimization for LLM workloads.
Experience building or operating AI evaluation systems: offline eval pipelines, LLM-as-judge approaches and their calibration against human judgment, regression testing for model or prompt changes, or A/B measurement of AI features.
Deep experience designing, building, and operating reliable distributed systems, including ownership of production services at meaningful scale, on-call responsibility, and incident leadership.
Demonstrated ability to use AI coding tools in day-to-day workflows and to validate, critique, and refine AI-generated output.

Location

San Francisco / Bay Area
San Jose
New York City
Seattle metros
Austin, TX
Washington DC metros
California
Massachusetts
New Jersey
Washington states
All other US locations

Experience Level

Staff level

Salary/Compensations

For candidates living in San Francisco / Bay Area, San Jose, New York City, or Seattle metros, the expected total cash compensation (base salary + variable pay, if applicable) range for the role is currently $249,900.00 - $323,400.00.
For candidates living in Austin, TX or Washington DC metros or in California, Massachusetts, New Jersey, or Washington states, the expected total cash compensation (base salary + variable pay, if applicable) range for the role is currently $225,300.00 - $291,500.00.
For candidates living in all other US locations, the expected total cash compensation (base salary + variable pay, if applicable) range for the role is currently $212,500.00 - $275,000.00.

About the Company

Thumbtack helps millions of people confidently care for their homes.
Thumbtack is the one app you need to take care of and improve your home — from personalized guidance to AI tools and a best-in-class hiring experience.
Every day in every county of the U.S., people turn to Thumbtack to complete urgent repairs, seasonal maintenance and bigger improvements.
We help homeowners know which projects to do, when to do them and who to hire from our growing community of 300,000 local service businesses.
If making an impact inspires you, join us. Imagine what we’ll build together.
At Thumbtack, our challenges span a wide range of areas, including search, recommendations, matchmaking, pricing, safety, content generation, fraud detection, and more.
The ML Infrastructure team is responsible for centralizing, standardizing and evolving AI/ML infrastructure that enables these experiences.
We empower product engineering teams by providing scalable, high-performance systems that drive AI innovation at scale.
To read more about some of the engineering challenges at Thumbtack, visit our engineering blog.

Equal Opportunity

Thumbtack embraces diversity. We are proud to be an equal opportunity workplace and do not discriminate on the basis of sex, race, color, age, pregnancy, sexual orientation, gender identity or expression, religion, national origin, ancestry, citizenship, marital status, military or veteran status, genetic information, disability status, or any other characteristic protected by federal, provincial, state, or local law.
We also will consider for employment qualified applicants with arrest and conviction records, consistent with applicable law.
Thumbtack is committed to working with and providing reasonable accommodation to individuals with disabilities.
If you would like to request a reasonable accommodation for a medical condition or disability during any part of the application process, please contact: recruitingops@thumbtack.com.
For information about how Thumbtack collects, uses, and shares personal information about job applicants, please see our Job Applicant Privacy Policy.
We put as much craftsmanship into candidate safety as we do into the hiring experience itself.
While scammers may try to impersonate our team, we’ll never ask you for money, banking info, or SSNs during hiring.
Check out our blueprint on how to spot the fakes.