Staff Machine Learning Engineer, Product
First seen by Alion on Oct 28, 2026.
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 Staff Machine Learning Engineer to own the end-to-end development of complex machine learning models that power personalized shopping experiences. In this role, you will research the best models for retrieval, ranking, and re-ranking; train and scale them in production systems; and iteratively improve their performance over time.
This is a senior individual contributor role with no direct reports. You'll lead by lending your technical judgment to discussions with Product, Engineering, and Design about solution design and you'll drive impact through hands-on delivery of models that enable the next era of personalized shopping experiences at ThredUp. This is a remote role based in the United States.
In This Role You'll Get To
- Own end-to-end model development: Given a user or business outcome, you'll lead the design, development, and deployment of production ML models.
- Build for scale: Deliver low-latency serving, high-throughput personalization algorithms that adapt to in-session behaviors, operate on a catalog of millions of one-of-a-kind items, and function as part of a broader recommender system.
- Connect models to business results: Assess potential for impact in offline evaluation and demonstrate that impact in the form of conversion and AOV in A/B testing.
- Influence our recommender system architecture: Identify opportunities to improve the recommender system architecture, from feature engines, to training & serving infrastructure, to evaluation.
- Mentor and collaborate: Build the skills of the cross-functional team by sharing your work, delivering thoughtful code reviews, and giving feedback on solution designs.
- Communicate clearly: Explain key decisions and technical tradeoffs to technical and non-technical stakeholders, including with VPs.
What We're Looking For
- 8+ years in machine learning engineering or data science, including 4+ years in e-commerce, social media, or two-sided marketplaces
- Demonstrated experience owning the development of models used for retrieval, ranking, or re-ranking, with an understanding of how they interact as part of a broader system
- Experience across the full ML development lifecycle, from feature engineering to evaluation in a production system. Familiarity with common tradeoffs associated with low-latency serving and how to manage them.
- Proven ability to drive towards outcomes in a fast-paced environment, collaborating across teams to manage dependencies and proactively manage tradeoff decisions
- Exceptional ability to communicate complex technical concepts clearly and effectively to a variety of audiences
- Eagerness to take on hard problems, learn new skills, and mentor others
- Ability to travel to a ThredUp office to work in-person at least once per quarter
- MS or PhD in Computer Science, Data Science, Engineering, or a related quantitative field; or equivalent industry experience
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 most Fridays off
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
[email protected] 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.