JD - Senior Software Engineer , ML

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Posted Yesterday job requisition :
JR15437
** Job Title
** JD - Senior Software Engineer 1, ML
** Job Description
****** About The Position** |
** As a Senior Software Engineer for personalization, you will own the design, development, and continuous improvement of the recommendation algorithm that powers the user's personalized product feed.

You'll work with a rich dataset of user-saved products and a live ingestion pipeline pulling from thousands of retailer feeds to build a system that learns each user's unique preferences across brand, category, color, price point, and fit.

This is a high-ownership, high-impact role. You will collaborate closely with product, engineering, and data teams to define what great personalization looks like — and then build it.
** Remote or Hybrid 3x a month
** In-office Expectations:
This position offers remote work flexibility; however, if you reside within a commutable distance to one of our offices in New York, Des Moines, Birmingham, Los Angeles, Chicago, or Seattle, the expectation is to work from the office two days per week.
**** About The Team: |******
* *** Our next-generation product discovery platform connects shoppers with the things they love across thousands of retail partners. Users save, organize, and share products they're excited about — and our platform turns those signals into a deeply personalized shopping experience. We ingest live product feeds from thousands of retailers and use a rich understanding of each user's taste to surface the right product at the right moment.

We're building the recommendation engine at the heart of this shopping experience — a system that understands not just what people save, but why they save it. This is a foundational hire that will shape how millions of users discover products they love.
**** About The Positions Contributions:
******** Accountabilities, Actions and Expected Measurable Results
******** Recommendation Algorithm Development
** 30%
*** Design and build the core personalization engine using user-saved product data as behavioral signals.
* Develop multi-signal recommendation models that incorporate brand affinity, product category, color palette, fit/sizing signals, price sensitivity, and trends.
* Implement and evaluate a range of approaches including collaborative filtering, content-based filtering, and hybrid neural architectures.
* Build and maintain product embedding models that capture rich semantic similarity across the retailer feed catalog.
* Develop cold-start strategies to generate high-quality recommendations for new users with limited save history.
**** Data Ingestion & Feature Engineering
** 25%
*** Design and maintain robust pipelines to ingest, normalize, and enrich product feeds from thousands of retail partners.
* Collaborate on a unified product taxonomy and attribute extraction layer that standardizes inconsistent retailer data into coherent features (category, color, material, fit, etc.).
* Leverage NLP and computer vision techniques to extract attributes from unstructured product descriptions and images.
* Partner with the data engineering team to maintain data quality, freshness, and catalog coverage at scale.
**** Personalized Feed & Ranking
** 25%
*** Build and own the ranking and re-ranking layer that assembles each user's personalized feed in real time.
* Develop and tune multi-objective ranking that balances relevance, novelty, diversity, and business goals (e.g., promoted/sponsored retailer partnerships).
* Implement feedback loops that continuously update user preference models based on implicit signals (saves, clicks, dwell time, shares).
* Build A/B testing solutions to rigorously evaluate ranking and recommendation changes against key engagement metrics.
**** Engineering Excellence
** 20%
*** Own production systems. Debug issues across indexing, retrieval, ranking, and serving layers
* Create clear documentation for pipelines, models, APIs, and system design.
* Contribute to best practices for ML systems,…