Doji
Founding Engineer
1mo ago
USASeniorpythonmachine learninginfrastructuredata pipelineapi development
Founding engineer role for building AI-powered fashion shopping products with broad technical responsibilities across AI, backend, and data.
Responsibilities
- We’re building the future of fashion shopping with AI avatars: personalized try-on, social discovery, and interfaces that make shopping feel alive.
- We’re a small, NYC-based team reimagining fashion shopping from the ground up. Our vision is playful, deeply personal, and centered on self-expression. To bring it to life, we combine advanced AI research, meticulous attention to detail, and an intuitive grasp of contemporary culture.
- Previously we’ve built products used by millions at Apple, DeepMind, Meta, Shopify, and startups. Now we’re backed by the investors behind OpenAI, Cursor, and SKIMS.
- We’re looking for a founding engineer who can move fast across the stack and go deep when the problem demands it. Early on, the work will be varied: one week you might ship a scrappy 0-to-1 prototype, the next you might optimize a feed ranker, debug a slow endpoint, or build infrastructure the rest of the team depends on. Over time, as the company grows, you’ll own the areas where you’re strongest.
- This is an in-person role from our office in NYC.
- The best person for this role is T-shaped: broad enough to move across AI, backend, data, and product surfaces when needed, with real depth in at least one of these areas:
- AI product systems - diffusion pipelines, batch LLM workflows, vector search, evals, structured outputs, and reliability work under real product constraints.
- Recsys and personalization - retrieval and ranking systems, embedding-based search, learned rankers, sequence modeling of user behavior, and online experimentation.
- Core product infrastructure - databases and query optimization, data warehousing, infra-as-code, deployment, observability. You know where latency, reliability, and cost problems usually hide.
Nice to have
- Have shipped iOS or other native mobile experiences
- Have worked on the infrastructure side of AI/ML - training pipelines, eval systems, data flywheels
Other
- Build end-to-end prototypes fast
- Go deep when necessary: optimize the feed ranker, profile a slow endpoint, debug a gnarly race condition, chase down a memory leak
- Own personalization end-to-end: retrieval, ranking, cold-start, and the tradeoffs that make recommendations feel fresh and relevant
- Ship infrastructure the team builds on top of: data pipelines, internal tools, eval systems
- Build LLM-powered systems that actually work in production
- Work directly with the founders to turn early product ideas into working software
- Contribute to product strategy and figure out what's worth building
- Can move between scrappy prototyping and deep technical work
- Ramp fast on unfamiliar domains
- Have taste for consumer products and opinions about what makes them good
- Have worked on consumer products, social products, marketplaces, or other user-facing systems at meaningful scale
- Are self-driven, high-agency, and good at getting unstuck
- Have genuine interest in fashion, avatars, or creative expression