Staff Software Engineer, Machine Learning Infrastructure

About the position

A home is the biggest investment most people make, and yet, it doesn’t come with a manual. That's why we’re building the only app homeowners need to effortlessly manage their homes — knowing what to do, when to do it, and who to hire. With Thumbtack, millions of people care for what matters most, and pros earn billions of dollars through our platform. And as one of the fastest-growing companies in a $600B+ industry — we must be doing something right. We are driven by a common goal and the deep satisfaction that comes from knowing our work supports local economies, helps small businesses grow, and brings homeowners peace of mind. We’re seeking people who continually put our purpose first: advocating for pros and customers, embracing change, and choosing teamwork every day. At Thumbtack, we're creating a new era of home care. If making an impact and the chance to do good inspires you, join us. Imagine what we’ll build together.

Responsibilities

• Define and drive the technical vision and architecture for Thumbtack's next-generation ML infrastructure
• Lead cross-functional initiatives spanning engineering, data science, and product teams to build scalable, enterprise-grade ML systems
• Architect and oversee implementation of critical ML infrastructure components including model serving systems and RAG systems that can scale
• Establish technical standards and best practices for ML engineering across the organization
• Mentor and provide technical leadership to engineering teams on ML infrastructure best practices
• Partner with senior leadership to align ML infrastructure capabilities with business objectives

Requirements

• 8+ years of engineering experience with significant focus on distributed systems
• 4+ years of hands-on experience building ML infrastructure or ML platforms at scale
• Deep expertise in at least one major programming language; proficiency in our core stack (Go, Python) preferred
• Proven track record of technical leadership on complex, cross-functional projects
• Strong architectural skills with experience designing scalable, reliable distributed systems
• Deep understanding of ML workflows, common frameworks, and operational challenges
• Experience mentoring teams and driving engineering excellence
• Track record of making strategic technical decisions with organization-wide impact

Nice-to-haves

• Experience building AI platforms that support hundreds of models in production
• Deep expertise with modern ML frameworks (PyTorch, TensorFlow) and MLOps tools
• Experience implementing generative AI capabilities at enterprise scale
• Track record of building high-performing technical teams
• Expertise with cloud-native architectures and major cloud providers (AWS, GCP)
• Experience driving technical strategy at fast-growing technology companies

Benefits

• Virtual-first working model coupled with in-person events
• 20 company-wide holidays including a week-long end-of-year company shutdown
• Library (optional use collaboration & connection hub) in San Francisco
• WiFi reimbursements
• Cell phone reimbursements (North America)
• Employee Assistance Program for mental health and well-being