Experience 3–6 yrs (3+ years)
About the role
structured by ORIWildcardAEO/GEO for E-Commerce and RetailFounding Applied ML Engineer$130K - $250K•0.50% - 4.00%•San Francisco, CA, USJob typeFull-timeRoleEngineering, Machine learningExperience3+ yearsVisaUS citizen/visa onlyConnect directly with founders of the best YC-funded startups.Apply to role ›Kaushik MahorkerCEOKaushik…
What you will do
- Building custom ML models to classify prompts, predict opportunity, and prioritize what brands should optimize for
- Building incrementality and attribution systems that connect AI visibility to revenue outcomes for ecommerce brands
- Building prompt discovery systems that identify and predict what shoppers are asking across AI commerce surfaces
- Designing ranking, scoring, and evaluation systems for noisy AI commerce outputs
- Modeling site traffic, conversion patterns, and performance trends from messy real-world data
What they are looking for
- Has prior founding experience, or was early at a Seed, Series A, Series B, or similarly fast-moving company
- Has strong full-stack experience and can ship independently across the stack
- Has applied ML or data science experience, especially with LLMs, ranking, retrieval, evals, attribution, experimentation, or product intelligence
- Can move between modeling, analysis, implementation, and product decisions
- Is high-agency, self-directed, and able to turn ambiguity into shipped product
- Is expert-level with AI coding tools and uses them to move significantly faster
- Has strong judgment on when to use AI and when not to
- Can reason about model behavior, failure modes, and quality without needing perfect data
- Moves fast, focuses on outcomes, and knows how to do more with less
- Brings new ideas constantly and can prioritize at a granular level
- Is resilient through changing priorities, new information, and mini-pivots
- Gets excited by ownership, ambiguity, and wearing multiple hats
Nice to have
- Applied ML, data science, or AI systems work in production or near-production environments
- Attribution modeling, traffic analysis, forecasting, causal inference, experimentation, or product analytics
- Experience taking ML models from offline analysis to production systems customers actually use
- Data pipelines, instrumentation, and signal collection from messy real-world sources
- Strong Python and SQL skills
- LLM workflows, retrieval systems, evals, fine-tuning, and model evaluation
- AI agents, including context management, orchestration, tool use, and evals
- Ecommerce, marketplaces, search, recommendations, analytics, or growth systems
Before you apply
- Interview process includes an Engineering Challenge and a one to two-day work trial.
Machine LearningLLMsRankingRetrievalAttributionExperimentationProduct IntelligenceCausal InferencePythonSQLTypeScriptExpressReact
Full posting text
Experience: 3+ years
$130K–$250K salary; 0.50%–4.00% equity.