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Principal Software Engineer - Machine Learning

March 7, 2026

About the Role: Fetch is building the future of personalized consumer experiences. We’re looking for a Principal Machine Learning Engineer to design and scale systems that power personalization, relevance, and ranking across our platform. This is a high-impact role where you’ll drive new initiatives, mentor other engineers, and shape the technical direction of ML at Fetch. This is a full-time role that can be held from one of our US offices or remotely in the United States. Role Responsibilities: • Build and scale ML infrastructure for personalization, search, ranking, and ad tech at consumer scale. • Design and implement zero-to-one systems, including real-time learning and data pipelines. • Lead technical design, architecture, and cross-team alignment for major ML initiatives. • Mentor engineers and help raise the bar on technical execution and design quality. • Partner with product and engineering teams to create dynamic systems that adapt to evolving user preferences. • Designing features and validating ideas with ChatGPT & Claude sandboxes. • Leveraging AI for code generation and technical prototyping. • Using AI assistants for systems architecture diagramming and design validation. • Exploring LLMs to enhance personalization, conversational search, and feature creation. Minimum Requirements: • Proven experience building and scaling ML infrastructure in support of personalization, relevance, search, or ad tech systems. • Deep hands-on expertise in data infrastructure, distributed systems, and large-scale data pipelines. • Experience working at a consumer product company with ML models operating at scale. • Prior contributions to ranking, personalization, or ad tech systems with measurable business impact. • Strong systems design skills, with a track record of leading architecture and communicating design tradeoffs. • Experience mentoring and elevating other engineers. • Success leading zero-to-one technical initiatives and delivering new infrastructure or ML systems from scratch. • Ability to operate in high levels of ambiguity with minimal direction, prioritizing effectively and driving impact. Preferred Requirements: • Familiarity with LLMs and their application in personalization, feature creation, and conversational search. • Experience with streaming/real-time learning systems. • Exposure to conversational search or large-scale information retrieval. • Previous work bridging model development with real-time serving systems. Apply tot his job

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