Founding AI / ML Engineer (Personalisation)
Location : SF Bay Area (hybrid) or In-Person ( Preferred )
Office : 505 Howard Street
Vision
Were building the reasoning layer for customer experience, a privacy-first, explainable system that understands why each person buys, safely simulates outcomes, and orchestrates touch points in real time at near-zero marginal cost. It plugs into any stack as a vendor-agnostic brain and compounds into an autonomous orchestrator that maximises LTV and margin.
We already have distribution in motion via enterprise CX Partners, top-agency advisors (WPP, OMC), and committed angels.
What youll do
- Own the ranking / reco core : features, training, eval, online inference.
- Design cost-aware intelligence (keep the why without an LLM per event).
- Build offline generation + fast online serving / caching; handle cold-start / backfills.
- Ship with design partners; instrument and prove lift quickly.
Requirements
Contextual data capture & featurisation (surveys / free text embeddings / NLP).Cost-aware pre-computation; avoid per-event LLM; cadence-based refresh.Customer clustering & query taxonomy; catalog-aware resolution limits.Offline / online architecture; fast (profile / query) lookups; cache coherency.Cold-start strategies, backfills, and refresh triggers on new cohorts / catalog updates.Content personalisation for key discovery / conversion surfaces; multi-channel outputs.Profile update logic after actions; consistent state across caches / stores.35 yrs ML with shipped impact in personalisation / CX (Klaviyo / Braze / Dynamic Yield / Uber / DoorDash-like).Stack : Python, PyTorch, SQL; Spark / Beam, Airflow, Kafka / Kinesis, Redis; GCP / AWS. Feast / Tecton a plus.Grit : bias to ship, founder hours, comfort with ambiguity.Nice to have
E-com / subscription, privacy-by-design, RL / bandits / causal, simulation / synthetic personas.
Comp & setup
Meaningful founding equity + salary. Part-time full-time post-raise or full-time now.