Staff Software Engineer Machine Learning Infrastructure

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About the Machine Learning Infrastructure Team

At Thumbtack were solving complex technical challenges across search ranking recommendations pricing optimization and spam detection. Our ML Infrastructure team leads the architectural vision and implementation of enterprisewide machine learning capabilities enabling teams to effectively experiment with and deploy ML models at scale. Were building nextgeneration infrastructure that powers Thumbtacks AIfirst future. For insights into our engineering challenges visit our engineering blog.

Challenge

As a Staff ML Infrastructure Engineer youll drive the technical vision and strategic direction of Thumbtacks machine learning platform. Youll architect solutions that democratize ML capabilities across the organization while establishing best practices and technical standards. Working closely with senior leadership youll shape our technical roadmap for generative AI adoption feature platform evolution and ML operational excellence.

What youll do

• Define and drive the technical vision and architecture for Thumbtacks nextgeneration ML infrastructure
• Lead crossfunctional initiatives spanning engineering data science and product teams to build scalable enterprisegrade 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

In order to be successful you must bring

• 8 years of engineering experience with significant focus on distributed systems
• 4 years of handson 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 crossfunctional 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 organizationwide impact

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