Senior Staff Machine Learning Engineer, Search & Discovery

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Define and drive the long term technical vision for Shopping ML across search, discovery, recommendations, and personalization.
Lead development of AI systems that fundamentally improve how customers discover products and shop on Instacart.
Architect large scale ML systems combining LLM reasoning, retrieval, ranking, recommendation models, and personalization.
Build and operate production ML systems powering real time shopping experiences across millions of users and products.
Identify foundational ML capabilities that unlock new customer experiences and accelerate experimentation across the organization.
Partner with senior leaders across product, engineering, and data science to shape technical strategy and roadmap.
Influence company wide ML architecture and contribute to major technical initiatives across Instacart.
Mentor senior/staff engineers through design reviews, architecture guidance, and hands-on collaboration.

Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field, or equivalent industry experience.
10+ years building and operating large scale machine learning systems in production.
Proven track record architecting ML systems that power core product experiences at global scale.
Deep expertise in areas such as recommendation systems, ranking models, embeddings, representation learning, or search systems.
Experience combining generative AI with traditional ML systems such as retrieval, ranking, and personalization.
Experience designing ML platforms that support large scale experimentation, training, and deployment.
Ability to influence senior engineering and product leaders and drive technical strategy.
Experience mentoring engineers and raising the technical bar across teams.

Experience building search, discovery, or recommendation systems for large consumer platforms.
Expertise in large language models, agentic AI systems, or tool using AI architectures.
Experience fine tuning and distilling LLMs for low latency production systems, balancing model quality, latency, and cost.
Experience building ML infrastructure supporting large scale experimentation and model deployment.
Background working on e-commerce, marketplaces, or large consumer platforms.
Recognized technical leadership through publications, patents, conference talks, or open source contributions.

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