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.
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.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
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