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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # DS/ML Scientist - Search Science - **Company:** Shipt, Inc. - **Location:** Birmingham, AL, United States (Remote available) - **Experience:** Expert - **Salary:** $115,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Automated Storage and Retrieval Systems, Information Retrieval, Python (Programming Language), Machine Learning, Recommender Systems, Tensorflow, Standard Sql, Feature Engineering, Pytorch, Large Language Models, Deep Learning, Information Technology - **Published:** July 2, 2026 - **Apply:** https://shipt.wd1.myworkdayjobs.com/Shipt_External/job/US-Remote/Senior-DS-ML-Scientist---Search-Science_R4257 ## About the Role * Bachelor's degree in a STEM field (Computer Science, Statistics, etc.) with a focus on machine learning * 3-5 years of experience applying Machine Learning to real-world problems * Strong coding fluency in Python and SQL * Deep familiarity with Deep Learning frameworks (PyTorch or TensorFlow) and their application to information retrieval, ranking and/or NLP * A solid grasp of Learning-to-Rank (LTR) concepts including rich feature engineering * Previous experience with Search or Recommender Systems in e-commerce settings * Experience with Multi-Objective Optimization: Understanding of the challenges of optimizing for multiple conflicting metrics (e.g., Relevance vs. Revenue), Data Science, Machine Learning (ML), Search EnginesBachelor's Degree or equivalent experience | Required ## Description ImpactAs a Senior Data Scientist on the Search Science team at Shipt, you will responsible for the algorithms that determine what customers see every day. You will be working to re-architecting Shipt's search stack to be LLM-native and value-aware. In this role you will build a state-of-the-art retrieval and ranking system from the ground up. You will partner with Senior Scientists and ML Engineers to push the boundaries of what a search engine can do. Search is the front door of Shipt-improvements you make here are immediately visible to leadership and impactful to the bottom line. How you can make an impact: Unified Ranking: Help design and implement multi-task learning (MTL) and multi-objective models that don't just optimize for clicks, but solve for complex trade-offs between organic relevance, ad revenue, and operational efficiency. In Depth Search Analysis: Identify opportunities, explore datasets, and report out findings to senior level leaders in the company which will influence our Search roadmaps. Deep Personalization: Move beyond generic relevance by integrating rich user signals through things like purchase history, dietary constraints, and real-time intent. Intentionally optimize our search system to predict not just what is relevant, but what is relevant for each customer. LLM-Native Search: Move beyond keyword matching by integrating Large Language Models into the core search loop. Work on projects such as generative retrieval, query expansion, and semantic understanding to handle complex, intent-driven user queries. Hybrid Retrieval Systems: Develop and tune sparse (lexical) and dense (vector) retrieval layers to maximize recall across our massive catalog, ensuring we surface the right products even for long-tail queries. Explore generative retrieval methodologies and their utilization., To foster connection while offering continued flexibility, hybrid team members have the following in-office expectations: Hybrid roles in Birmingham, AL typically work in-office at least 2 days per week, with core in-office days on Wednesdays and Thursdays. Hybrid roles in Minneapolis, MN typically work in-office at least 1 day per week on either Tuesday, Wednesday, or Thursday. Hybrid roles in San Francisco, CA typically work in-office at least 1 day per week between Monday and Thursday. Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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