T
ThredUp
Senior Staff Machine Learning Architect
Skills
E-commerce WebsitesData ScienceMachine Learning
2 months ago
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Important information
Salary:
$250,000 – $300,000 / year
Location:
San Francisco, CA, USA
Work mode:
Onsite
Published on:
19 August 2026
What they need
Who you are
- 10+ years in Data Science, Machine Learning Engineering, or Software Engineering, including 5+ years focused specifically on recommender systems
- MS or PhD in Computer Science, Data Science, Engineering, or a related quantitative field; or equivalent industry experience
- We are open to considering candidates with prior position titles and experience as an Applied Scientist, Software Engineer, or Data Scientist
- Demonstrated experience architecting end-to-end recommender system pipelines that span multiple services. Deep expertise in machine learning models used across retrieval, ranking, and reranking
- A track record of setting technical direction across teams or product lines. Examples include: architecture decisions adopted org-wide, cross-team platform migrations, or serving as a technical authority across multiple engineering groups
- Experience balancing ML metrics (recall, precision, NDCG) against business metrics (conversion, AOV, etc.)
- Knowledge of how to build distributed systems at scale: low-latency serving, feature stores, vector databases, and streaming pipelines
- Excellent written and verbal communication. Able to drive alignment across technical and non-technical stakeholders without formal authority
- Experience building highly adaptive recommender systems, typically involving some aspect of real-time feature generation and reinforcement learning is a plus
- Experience working with large product catalogs with a high degree of cold start problems; this may but need not be in an eCommerce setting is a plus
- Hands-on experience working with OpenSearch is a plus
- Open-source contributions or publications in recommender systems, retrieval, or ranking is a plus
What the job involves
- We're looking for a Machine Learning Architect to define the technical strategy for our recommender system as we seek to personalize the experience for everyone on the ThredUp platform. In this role, you'll set the architectural direction that our personalization teams build on, and you'll be a key technical advisor to other teams shaping the data, backend, and frontend systems that power our recommender system
- You'll partner closely across engineering leadership, data science, and product to make sure our recommendation infrastructure scales with the business, balancing relevance, diversity, and business outcomes like conversion and AOV, while staying flexible enough to adapt to emerging product innovations
- This is a senior individual contributor role with a major opportunity to directly impact company performance. You won't have direct reports, but you'll drive impact by shaping how dozens of engineers and data scientists build the next era of personalized shopping experiences at ThredUp. We're targeting candidates at Senior Staff to Principal level. Final title, level, and compensation will be determined based on experience, scope, and demonstrated impact
- Define and own the long-term technical architecture for recommendation systems spanning retrieval, ranking, re-ranking, and real-time serving across multiple surfaces
- Act as the connective tissue across teams that build and operate recommender system components and influence investment decisions across the org by authoring architecture RFCs and leading technical reviews
- Design for scale: low-latency serving, high-throughput candidate retrieval, real-time feature freshness, and a catalog of millions of unique items listed at any point in time
- Partner with product and business stakeholders to translate merchandising, catalog, and revenue goals into ML system requirements
- Mentor across teams; raise the technical bar company-wide
- Be hands-on: read the latest recommender system research, prototype, review code and designs, and dig into production issues when the problem calls for it
Benefits
- Competitive salary (we leverage market data) + stock
- Employee stock purchase plan
- Flexible PTO (take the time you need) + 13 company holidays (US offices)
- Paid Sabbatical after 3 years of full time employment
- Generous paid parental leave for new mothers and fathers
- Medical, dental, vision, 401k, life and disability insurance offered
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