About the role
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 Software Engineer on the ML Infrastructure team, you will work closely with product and platform engineering teams to build and evolve core AI platform capabilities. You will help design and improve systems that allow teams to develop, run, and scale GenAI-powered applications in production. Your work will directly support AI-driven experiences used by millions of customers and pros across the Thumbtack ecosystem. 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 1 to 3 years of professional software engineering experience. Strong fundamentals in data structures, algorithms, and software design. Proficiency in at least one major programming language, and the ability to work across multiple languages. Our primary stack includes Go and Python. Experience working with relational or NoSQL databases such as Postgres or DynamoDB. Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output Comfort operating in a fast-paced environment with a certain level of ambiguity, especially when learning and picking up new technologies when projects require it. You operate with a bias to action, quickly learning what is needed and taking decisive steps to move work forward in ambiguous, fast-paced environments. Expected salary ranges For candidates living in San Francisco / Bay Area, San Jose, New York City, or Seattle metros, the expected salary range for