What You'll Own
Build custom ML models to classify prompts, predict opportunity, and prioritize what brands should optimize for
Design and ship ranking, scoring, and evaluation systems for noisy AI commerce outputs
Build incrementality and attribution systems that connect AI visibility to revenue outcomes for ecommerce brands
Develop data pipelines to collect signals and turn them into usable product intelligence
Move between modeling, analysis, implementation, and product decisions without waiting for direction
Own core AI workflows and make them reliable with queues, retries, observability, evals, and workflow orchestration
Must-Have
3+ years shipping production systems with strong full-stack experience and ability to move independently across the stack
Applied ML or data science experience, especially with LLMs, ranking, retrieval, evals, attribution, experimentation, or product intelligence
Strong Python and SQL skills, with ability to reason about model behavior, failure modes, and quality without needing perfect data
High agency, self-directed mindset; able to turn ambiguity into shipped product and make high-impact daily decisions
Expert-level with AI coding tools and strong judgment on when to use AI and when not to
Prior founding experience or was an early engineer at a Seed, Series A, or Series B company
Nice-to-Have
Experience taking ML models from offline analysis to production systems customers actually use
Data pipelines, instrumentation, and signal collection from messy real-world sources
Attribution modeling, traffic analysis, forecasting, causal inference, or experimentation background
Ecommerce, marketplaces, search, recommendations, analytics, or growth systems experience
Enough full-stack experience to ship customer-facing product, APIs, or internal tools across TypeScript, Express, React when needed