Principal Software Engineer; Machine Learning

Requirements

• Proven experience building and scaling ML infrastructure in support of personalization, relevance, search, or ad tech systems
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• Deep hands-on expertise in data infrastructure, distributed systems, and large-scale data pipelines
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• Experience working at a consumer product company with ML models operating at scale
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• Prior contributions to ranking, personalization, or ad tech systems with measurable business impact
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• Strong systems design skills, with a track record of leading architecture and communicating design tradeoffs
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• Experience mentoring and elevating other engineers
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• Success leading zero-to-one technical initiatives and delivering new infrastructure or ML systems from scratch
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• Ability to operate in high levels of ambiguity with minimal direction, prioritizing effectively and driving impact
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• Familiarity with LLMs and their application in personalization, feature creation, and conversational search
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• (Desirable) Experience with streaming/real-time learning systems
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• (Desirable) Exposure to conversational search or large-scale information retrieval
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• (Desirable) Previous work bridging model development with real-time serving systems

• Fetch is building the future of personalized consumer experiences
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• We’re looking for a Principal Machine Learning Engineer to design and scale systems that power personalization, relevance, and ranking across our platform
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• This is a high-impact role where you’ll drive new initiatives, mentor other engineers, and shape the technical direction of ML at Fetch
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• Build and scale ML infrastructure for personalization, search, ranking, and ad tech at consumer scale
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• Design and implement zero-to-one systems, including real-time learning and data pipelines
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• Lead technical design, architecture, and cross-team alignment for major ML initiatives
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• Mentor engineers and help raise the bar on technical execution and design quality
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• Partner with product and engineering teams to create dynamic systems that adapt to evolving user preferences
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• Designing features and validating ideas with ChatGPT & Claude sandboxes
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• Leveraging AI for code generation and technical prototyping
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• Using AI assistants for systems architecture diagramming and design validation
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• Exploring LLMs to enhance personalization, conversational search, and feature creation