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Senior Machine Learning Engineer II, Search & Recommendations Ranking

1 day, 21 hours ago
United States
Full-time
Lead
Machine Learning Engineer
Data Science and Analytics
Deep Learning LLM Machine Learning Pandas Python PyTorch SQL TensorFlow XGBoost
Apply Now
instacart.careers

instacart.careers

Instacart is a leading grocery technology company in North America that works with grocers and retailers to transform how people shop. They partner with over 1,000 national, regional, and local retail banners to facilitate online shopping, delivery, an...

Internet Software & Services
1K-5K
View All Jobs 124

Description

  • Architect the ranking backbone that unifies query understanding, personalization, multi-objective ranking, ads, and merchandising into a single adaptive platform.
  • Design and build a search autosuggest system optimized for personalization and value-based relevance.
  • Design long-horizon objective functions and build uplift or causal value models focused on incrementality, LTV, and habit formation.
  • Develop production-grade multi-task learning systems to jointly learn relevance, propensity, margin, and churn risk.
  • Own the inference layer, including goal-aware re-rankers, diversity and quality constraints, safe exploration, and low-latency optimization.
  • Advance evaluation through online experiments, long-horizon cohort metrics, counterfactual evaluations, and attribution pipelines.
  • Partner with ads, infrastructure, product, and design teams to translate business goals into ranking policies and measurable ROI.
  • Mentor ML engineers in ranking, causal inference, and scalable serving systems.

Requirements

  • 5+ years applying ML at scale, including 3+ years in technical leadership, with a track record improving ranking or recommendation systems in production.
  • Experience applying multi-objective or constrained optimization to balance relevance, revenue, margin, and user experience.
  • Experience with online testing and attribution beyond CTR.
  • Strong coding ability in Python and data fluency with SQL and Pandas.
  • Experience with classic ML techniques such as XGBoost and deep learning frameworks such as TensorFlow or PyTorch.
  • Excellent analytical skills and strong cross-functional communication abilities.
  • Preferred: expertise in multi-task learning architectures such as MMOE or PLE, shared encoders, calibration, counterfactual evaluation, uplift or causal modeling, and/or contextual bandits.
  • Preferred: experience building low-latency ranking services, including feature stores, caching, vector and lexical retrieval, re-ranking, and A/B testing infrastructure.
  • Preferred: hands-on experience with LLMs as feature or recall enhancers, such as embeddings or adapter tuning.

Benefits

  • Highly market-competitive compensation and benefits.
  • Remote role with Flex First work flexibility.
  • Eligible for a new hire equity grant.
  • Eligible for annual refresh grants.
  • Base pay range varies by permanent work location, with US ranges provided for multiple states.

Interested in this position?

Apply directly on the company website

Apply Now

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