Senior Machine Learning Engineer II, Search & Recommendations Ranking

Навыки

• A/B-тесты
• Атрибуция
• XGBoost / LightGBM / CatBoost
• CPC / CPM / CTR
• Лидерство
• LLM
• LTV

О компании и продукте

• The Search & Personalization ML team is Instacart’s engine for state-of-the-art multi-task, multi-objective ranking—unifying search, discovery, recommendation, ads, and merchandising into a single value-aware platform. Partnering with world-class engineers, scientists, and PMs, we build the ranking backbone that powers every pixel of the shopping journey, optimizing not just for clicks, but for incremental GTV, basket lift, and retention over the long run.
• Foundational Ranking Backbone Models: Multi-task/multi-objective models (shared encoders + task heads) that jointly learn relevance, conversion, margin contribution, churn risk, and ad quality, enabling consistent decisions across search and recommendations.
• Value-Aware Optimization: Uplift and long-horizon value models that steer decisions toward incrementality and LTV, with calibrated constraints on quality, diversity, fairness, and spend pacing—plus guardrails for safe exploration.
• LLM-Enhanced Retrieval & Features: Using LLMs to enrich query and item semantics for long-tail recall, generate features for cold-starts, and feed the ranker with reasoning-rich context, while remaining the source of truth for final ordering.

Задачи

• We're transforming the grocery industry
• At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together
• Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community
• We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers
• Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward
• If you’re ready to do the best work of your life, come join our table
• Instacart is a Flex First team
• There’s no one-size fits all approach to how we do our best work
• Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events
• Learn more about our flexible approach to where we work

Требования

• 5+ years applying ML at scale (3+ years in technical leadership), 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.\
• Graduate degree (Masters or PhD) in machine learning, statistics, computer science, information retrieval, or a closely related field
• Experience building low-latency ranking services, including feature stores, caching, vector + lexical retrieval, re-ranking, and A/B testing infrastructure, with expertise in constraint-aware inference
• Hands-on experience with LLMs as feature/recall enhancers (e.g., embeddings, adapter tuning) while maintaining clarity on when the ranker should arbitrate

Будет плюсом

• Expertise in multi-task learning architectures (e.g., MMOE/PLE, shared encoders), calibration, counterfactual evaluation, uplift/causal modeling, and/or contextual bandits for exploration
• Instacart provides highly market-competitive compensation and benefits in each location where our employees work
• This role is remote and the base pay range for a successful candidate is dependent on their permanent work location
• Please review our Flex First remote work policy here
• Offers may vary based on many factors, such as candidate experience and skills required for the role
• Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants
• Please rea d more about our benefits offerings here
• For US based candidates, the base pay ranges for a successful candidate are listed below
• CA, NY, CT, NJ
• OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
• All other states

Условия

• 207,000 — $253,500 USD
• 198,000 — $243,000 USD
• 190,000 — $233,000 USD
• 173,000 — $212,000 USD

Паспорт вакансии

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