Founding Applied ML Engineer - Full-stack Python and SQL

 

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

 

 

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

 

 

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