Staff Software Engineer, AI/ML Infrastructure

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.

About the Machine Learning Infrastructure Team

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 .

The challenge

As a Staff Software Engineer on the team, you will be a senior technical leader on a team whose systems sit in the critical path of every AI-powered experience at Thumbtack. You will set technical direction across both of the team's surfaces: the AI/ML platform (LLM gateway, model training and serving, feature and data workflows, orchestration, observability) and the AI evaluation platform (trace ingestion, scorer infrastructure, LLM-as-judge calibration, pre-deploy regression gates, and self-serve evaluation tooling for product teams).

This is not a role where architecture happens on a whiteboard and someone else builds it. You will design, write, and ship significant systems yourself while raising the technical bar of the engineers around you. You will partner with applied scientists, product engineering teams, and engineering leadership to define multi-quarter roadmaps, make consequential build/buy/adopt decisions across a fast-moving vendor and open-source landscape, and ensure the platform scales with the company's rapidly growing AI ambitions.

What you’ll do

Build and evolve core AI platform capabilities that enable teams to develop, run, and scale GenAI-powered applications across Thumbtack.

Contribute to the design, development, and deployment of scalable tools and infrastructure to support the efforts of our 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 that help product teams harness advances in AI.

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.

In order to be successful, you must bring

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.

Expected salary ranges

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.