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Founding AI/ML Engineer ( Personalisation ) (San Francisco)
Founding AI/ML Engineer ( Personalisation ) (San Francisco)codax • San Francisco, CA, United States
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Founding AI / ML Engineer ( Personalisation ) (San Francisco)

Founding AI / ML Engineer ( Personalisation ) (San Francisco)

codax • San Francisco, CA, United States
22 hours ago
Job type
  • Full-time
  • Part-time
Job description

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.

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