Senior Machine Learning Engineer, Instacart

• 4+ years applying ML at scale with a Master’s degree, or 2+ years for PhD, with a proven track record improving ranking or recommendation systems in production
• Demonstrated success in applying multi-objective or constrained optimization to balance relevance, revenue, margin, and user experience; experience with online testing and attribution beyond CTR
• Strong coding (Python) and data fluency (SQL/Pandas), with expertise in classic ML techniques (e.g. , XGBoost) and deep learning frameworks (TensorFlow/PyTorch)
• Excellent analytical skills and strong cross-functional communication abilities

Desirable

• 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 (e.g., incrementality, LTV, habit formation) and build uplift/causal value models that move beyond short-term engagement
• Develop production-grade Multi-Task Learning (e.g., shared encoders, MMOE/PLE task heads) to jointly learn relevance, propensity, margin, and churn risk—ensuring calibration, constraints, and explainability
• Own the inference layer: goal-aware re-rankers, diversity and quality constraints, safe exploration, and millisecond-class latency optimization
• Advance evaluation practices: online experiments, long-horizon cohort metrics, counterfactual evaluations, and attribution pipelines for tracking incremental GTV and retention
• Partner across ads, infrastructure, product, and design teams to translate business goals into ranking policies and measurable ROI
• Mentor ML engineers to build expertise in ranking, causal inference, and scalable serving systems