Staff Software Engineer, Discovery Platform

Whatnot•Seattle, WA

2d•$230,000 - $290,000•Hybrid

About The Position

Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.

Requirements

A bachelor's degree in Computer Science, a related field, or equivalent practical experience.
8+ years of full-time software engineering experience, including building and operating large-scale distributed systems in production.
A track record of leading substantial technical initiatives across teams, defining problems clearly, aligning partners, and shipping solutions through ambiguity.
Experience designing reliable, low-latency backend systems such as search infrastructure, retrieval services, event-driven systems, or streaming data pipelines. Experience with search or recommendations at scale is a strong plus.
Hands-on experience with technologies such as OpenSearch or Elasticsearch, Redis or Valkey, and Kafka or similar streaming systems. We value strong fundamentals and relevant systems experience over an exact match to our tools.
An understanding of how recommendation systems fit together, including candidate generation, ranking, and feature serving, and the ability to partner effectively with machine learning engineers.
Strong product instincts: you connect performance and reliability decisions to whether buyers discover things they want and whether sellers reach the right audience.
A commitment to hands-on engineering, with the judgment to write code, document architectural decisions, and drive alignment when needed.
Experience mentoring engineers and improving the quality of designs, code, and operational practices.

Nice To Haves

Experience with search or recommendations at scale is a strong plus.

Responsibilities

Design and evolve search and serving infrastructure that performs reliably through live shopping traffic spikes, including our largest sales events.
Build retrieval systems that let feed and search teams add candidate sources safely and quickly.
Partner with ranking and machine learning engineers to bring models and features into production with the latency and freshness they need.
Set technical direction for Discovery Platform and influence roadmaps across partner teams, using data and product outcomes to guide decisions.
Own complex systems end to end, from architecture and implementation through production operations and on-call.
Raise the engineering bar through hands-on contributions, design and code reviews, and mentorship.

Benefits

Generous Holiday and Time off Policy
Health Insurance options including Medical, Dental, Vision
Work From Home Support
Home office setup allowance
Monthly allowance for cell phone and internet
Care benefits
Monthly allowance for wellness
Annual allowance towards Childcare
Lifetime benefit for family planning, such as adoption or fertility expenses
Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
Monthly allowance to dogfood the app
16 weeks of paid parental leave + one month gradual return to work company leave allowances run concurrently with country leave requirements which take precedence.