ML / AI Engineer

Wintermeyer Ventures; San Francisco (CA); On-site; USD 200,000 - 300,000; Full time

Job summary

Wintermeyer Ventures seeks a founding-team ML / AI Engineer in San Francisco, on-site only. You will architect and build the intelligent systems powering core product experiences, owning the full stack from data pipelines to user-facing AI features.

You will lead model selection, embeddings, RAG pipelines, and scalable inference, working with product and design to create delightful, tangible AI features for consumer SaaS products. Salary $200k-$300k plus equity; visa sponsorship not available.

Qualifications

• 3+ years in ML/AI roles shipping user-facing ML features.
• Experience taking ML-powered features from 0 to 1 with measurable impact.
• Hands-on development with embeddings or personalization models.
• Data pipelines, vector databases, RAG, and semantic search experience.
• Familiarity with inference infrastructure and production deployment.
• Strong CS, Math, EECS or equivalent technical foundation.

Responsibilities

• Architect and build ML and retrieval systems powering core product experiences.
• Design data pipelines to ingest, classify, enrich, and summarize large user data.
• Build scalable inference infrastructure for real-time and batch workloads.
• Lead model selection, embeddings, and evaluation frameworks.
• Prototype quickly, then harden and ship what works.
• Collaborate with product, design, and engineering to create useful features.
• Lay the groundwork for ML excellence inside a small senior team.

Skills

ML/AI engineering

Personalization features

Embeddings

Vector databases

RAG pipelines

Python programming

Education

CS/EECS background

Tools

FastAPI

PostgreSQL

Vector databases

Job description

About the Role

This is a founding-team ML / AI Engineer position at a consumer SaaS startup, where you will architect and build the intelligent systems that power core product experiences. You will own the full stack from data pipelines to user-facing AI features, working closely with product and design to make complex ML feel intuitive and magical.

What You'll Do

• Architect and build ML and retrieval systems that power the core product experience.
• Design and evolve data pipelines that ingest, classify, enrich, and summarize large volumes of user data.
• Build scalable inference infrastructure for both real-time and batch workloads.
• Lead model selection, fine-tuning, embeddings, RAG pipelines, evaluation frameworks, and quality measurement.
• Prototype quickly to explore new ML-powered product ideas, then harden and ship what works.
• Apply product judgment to make complex AI systems feel simple and delightful to end users.
• Collaborate with product, design, and engineering to create features that feel alive and deeply useful.
• Lay the groundwork for ML excellence inside a small, senior team.

What We're Looking For

• 3+ years in ML / AI roles building and shipping ML-powered features such as personalization, ranking, search, or recommendations at consumer product or AI companies.
• Demonstrated experience taking ML-powered product features from 0 to 1 with tangible, user-facing results.
• Hands‑on custom ML model development with embeddings, recommendation systems, or personalization models (not limited to LLM prompting or wrappers).
• Experience with data pipelines, vector databases, RAG, and semantic search infrastructure.
• Familiarity with inference infrastructure and deployment in production environments.
• Strong CS, Math, EECS, or equivalent technical foundation.
• Background at a consumer product company or a leading AI company, ideally with early‑stage startup experience.
• Ability to work backwards from user experience to determine what ML system to build.
• Comfort with ambiguity, fast iteration, and end‑to‑end ownership on a small, high‑trust team.
• Proficiency with Python; experience with FastAPI, PostgreSQL, and vector databases is a strong plus.

Compensation & Benefits

Base salary: $200,000 to $300,000 USD annually, plus equity. Visa sponsorship is not available for this role.

Location

On‑site in San Francisco, CA. Remote work is not available for this position.