Machine Learning Architect, Personalization

ThredUp; Oakland (CA); Hybrid; USD 250,000 - 300,000; Full time

Benefits offered by this job

4-day work week

Hybrid work environment

Employee stock purchase plan

Comprehensive benefits

Job summary

ThredUp is seeking a Senior Machine Learning Architect to define the technical strategy for our recommender system and to guide the architecture across data science, backend, and product teams.

You will shape scalable, low-latency architecture, balance ML and business metrics, and mentor engineers and data scientists while staying hands-on in prototype work and production issue resolution at ThredUp.

Qualifications

• 10+ years in Data Science, ML Engineering, or Software Engineering with 5+ years in recommender systems.
• MS or PhD in Computer Science, Data Science, Engineering, or related field, or equivalent experience.
• Experience architecting end-to-end recommender system pipelines and setting technical direction across teams.
• Balance ML metrics with business metrics and design distributed, scalable systems.
• Strong communication across technical and non-technical stakeholders.

Responsibilities

• Define long-term technical architecture for recommendation systems including retrieval, ranking, and real-time serving.
• Collaborate across teams, author architecture RFCs, and lead technical reviews.
• Design for scale with low-latency serving, high-throughput retrieval, and large item catalogs.
• Translate merchandising and revenue goals into ML system requirements.
• Mentor teams and contribute hands-on by prototyping and reviewing designs and code.

Skills

Data Science

Machine Learning Engineering

Software Engineering

Recommender systems

Architecting systems

Communication

Education

MS or PhD in Computer Science or related field

Tools

OpenSearch

Job description

About ThredUp

ThredUp is transforming resale with technology and a mission to inspire the world to think secondhand first. By making it easy to buy and sell secondhand, ThredUp has become one of the world's largest online resale platforms for apparel, shoes and accessories. Sellers love ThredUp because we make it easy to clean out their closets and unlock value for themselves or for the charity of their choice while doing good for the planet. Buyers love shopping value, premium and luxury brands all in one place, at up to 90% off estimated retail price. Our proprietary operating platform is the foundation for our managed marketplace and consists of distributed processing infrastructure, proprietary software and systems and data science expertise. With ThredUp’s Resale-as-a-Service, some of the world's leading brands and retailers are leveraging our platform to deliver customizable, scalable resale experiences to their customers. ThredUp has processed over 172 million unique secondhand items from 55,000 brands across 100 categories. By extending the life cycle of clothing, ThredUp is changing the way consumers shop and ushering in a more sustainable future for the fashion industry.

About ThredUp

ThredUp is transforming resale with technology and a mission to inspire the world to think secondhand first. By making it easy to buy and sell secondhand, ThredUp has become one of the world's largest online resale platforms for apparel, shoes and accessories. Sellers love ThredUp because we make it easy to clean out their closets and unlock value for themselves or for the charity of their choice while doing good for the planet. Buyers love shopping value, premium and luxury brands all in one place, at up to 90% off estimated retail price. Our proprietary operating platform is the foundation for our managed marketplace and consists of distributed processing infrastructure, proprietary software and systems and data science expertise. With ThredUp’s Resale-as-a-Service, some of the world's leading brands and retailers are leveraging our platform to deliver customizable, scalable resale experiences to their customers. ThredUp has processed over 172 million unique secondhand items from 55,000 brands across 100 categories. By extending the life cycle of clothing, ThredUp is changing the way consumers shop and ushering in a more sustainable future for the fashion industry.

Recognized on TIME Most Influential Companies of 2023, Digiday's WorkLife 50 2023, TIME's Best Inventions of 2022, and Lattice's People Success Awards 2022.

How You Will Make An Impact

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.

In This Role You’ll Get To

• 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.

What We're Looking For

• 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.

At ThredUp, your base pay is one part of your total compensation package. This role pays between $250,000 and $300,000, and your actual base pay will depend on your skills, qualifications, experience, and location.

Many ThredUp employees also have the opportunity to own shares of ThredUp stock, ThredUp employees are eligible for discretionary restricted stock unit awards, as well as a discount when purchasing ThredUp stock if voluntarily participating in ThredUp’s Employee Stock Purchase Plan. Subject to eligibility requirements, you’ll also receive other benefits: Comprehensive medical & dental coverage, vision, 401k, life and disability insurance.

This role is not eligible for visa sponsorship.

What We Offer

• 4-day work week, with Fridays off
• Hybrid work environment: 3 days in the office and 1 day remote each week
• Competitive salary (we leverage market data)
• Many ThredUp employees also have the opportunity to own shares of ThredUp stock and are eligible for discretionary restricted stock unit awards
• Employee stock purchase plan
• Flexible PTO (take the time you need) + 13 company holidays
• 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
• We live by our Core Values of Transparency, SpeakingUP, Thinking Big, Infinite Learning, Influencing Outcomes & Seeking the Truth

We believe diversity, inclusion and belonging is key for our team

At ThredUp, our mission has been built on extending the lives of millions of unique clothing items. Much like our inventory, we are proud to have fostered a workplace that is one-of-a-kind. As a company focused on diversity, inclusion and belonging, we are committed to ensuring our employees are comfortable bringing their authentic selves to work every day. A unique perspective is critical to solving complex problems and inspiring a new generation to think secondhand first. Be you.

If you are a candidate with a disability and have a reasonable accommodation request for the job application process, please email [e-mail] the specific details of your disability related accommodation request. This email address is reserved for candidates with disabilities only. General application inquiries will not receive a response.