Software Engineer, AI/ML Infrastructure (US-Based)
About The Position
Thumbtack is hiring a Software Engineer for its Machine Learning Infrastructure team. The team centralizes, standardizes, and evolves AI/ML infrastructure for product experiences across areas such as search, recommendations, matchmaking, pricing, safety, content generation, and fraud detection. The role works closely with product and platform engineering teams to build core AI platform capabilities and systems that help teams develop, run, and scale AI-powered applications in production. The work supports AI-driven experiences used by millions of customers and service professionals. The engineer will contribute to scalable infrastructure and tooling for applied scientists, spanning traditional ML training and serving, feature and data workflows, CI/CD, orchestration, deployment, and evaluation. The role works across backend services, execution infrastructure, and AI model and tooling integrations, and partners with senior engineers to assess emerging infrastructure frameworks. Projects are expected to focus on business impact and measurable outcomes.
Requirements
- At least 2 years of professional software engineering experience.
- Strong fundamentals in data structures, algorithms, and software design.
- Proficiency in at least one major programming language and ability to work across multiple languages; the primary stack includes Go and Python.
- Experience with relational or NoSQL databases such as Postgres or DynamoDB.
- 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, ambiguous environment and learning new technologies as projects require.
- Bias to action, with the ability to learn quickly and take decisive steps to move work forward in ambiguous, fast-paced environments.
Responsibilities
- Build and evolve core AI platform capabilities that enable teams to develop, run, and scale AI-powered applications across Thumbtack.
- Contribute to designing, developing, and deploying scalable tools and infrastructure for applied scientists, including ML training and serving systems, feature and data workflows, CI/CD, orchestration, deployment, and evaluation tooling.
- Work across backend services, execution infrastructure, and 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 focus on business impact and measurable outcomes.
- Solve complex technical problems and stay current with advances in AI infrastructure.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
