Staff Software Engineer, Machine Learning Infrastructure

Summary

Join Thumbtack's Machine Learning Infrastructure team as a Staff ML Infrastructure Engineer and drive the technical vision and strategic direction of our next-generation ML platform. You will architect solutions to democratize ML capabilities, establish best practices, and shape our technical roadmap for generative AI. This role involves leading cross-functional initiatives, mentoring engineering teams, and partnering with senior leadership. The ideal candidate possesses extensive experience in distributed systems, ML infrastructure, and technical leadership. Thumbtack offers a virtual-first work model with various benefits and perks.

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

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

Preferred Qualifications

• 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