Founding Machine Learning Engineer

Stealth Startup

San Francisco (CA)

Presencial

USD 200 000 - 240 000

Tempo integral

há 27 horas
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Vantagens oferecidas por esta oferta de emprego

Equity
High ownership and direct impact

Resumo da oferta

Stealth Startup in San Francisco is seeking a Machine Learning Engineer to build, ship, and operate ML models powering our EV marketplace.

You will own data, training, deployment, monitoring, and ML services end to end, collaborating with product, data, and full-stack engineers to shape our ML platform as we grow.

Ideal candidates have 3+ years shipping production ML, strong Python, and hands-on with PyTorch, TensorFlow, or scikit-learn; onsite in SF.

Qualificações

  • 3+ years building production ML systems.
  • Proven track record shipping models or ML services to production.
  • Strong Python programming.
  • Experience with PyTorch, TensorFlow, or scikit-learn; feature pipelines and model serving.
  • Based in the San Francisco Bay Area and onsite in San Francisco.
  • Bachelor's degree in Computer Science or related field.
  • History of multi-year ownership in prior roles.

Responsabilidades

  • Design, train, and deploy ML models powering core marketplace experiences.
  • Build production ML services and pipelines with feature pipelines and model serving.
  • Develop AI features and LLM-powered product capabilities.
  • Own model quality in production: evaluation, retraining, and reliability.
  • Help set ML engineering standards for a small, fast-moving team.

Conhecimentos

Python in production
Production ownership
Onsite SF involvement

Formação académica

B.S. in CS

Ferramentas

PyTorch
TensorFlow
scikit-learn

Descrição da oferta de emprego

Machine Learning Engineer — Stealth Startup, San Francisco

Employment type: Full-time

About us

We're an early-stage San Francisco startup building an AI-powered marketplace for electric vehicles. We're using machine learning to make buying and selling EVs simpler, faster, and more transparent, and we're hiring engineers who want to own real production systems from day one.

The role

As a Machine Learning Engineer, you'll build, ship, and run the models and ML services behind our marketplace. You'll own work end to end: data and features, training, evaluation, deployment, and monitoring in production. You'll work closely with product, data, and full-stack engineers, and you'll have a direct hand in shaping our ML platform as we grow.

What you'll do
  • Design, train, and deploy ML models that power core marketplace experiences, such as search, ranking, recommendations, pricing, and AI-assisted product features
  • Build and maintain production ML services and pipelines, including feature pipelines, model serving, and monitoring
  • Build applied AI and LLM-powered product features where they add real value for buyers and sellers
  • Own model quality in production: evaluation, experimentation, retraining, and reliability
  • Help set ML engineering standards and tooling for a small, fast-moving team
What we're looking for (required)
  • 3+ years of hands-on experience as an ML/AI engineer building production ML systems (not research-only)
  • A track record of shipping models or ML services to production and owning them after launch
  • Strong Python, used in production ML/AI work
  • Hands-on experience with modern ML frameworks and tooling (for example PyTorch, TensorFlow, or scikit-learn), plus feature pipelines and model serving
  • Based in the San Francisco Bay Area and able to work onsite in San Francisco
  • Bachelor's degree in Computer Science or a closely related technical field
  • A history of sustained ownership in prior roles (multi-year tenure preferred)
Nice to have
  • 6–12 years of relevant engineering experience
  • Experience with marketplaces, recommendations, search, or ranking systems
  • Experience building LLM or applied AI product features
  • Experience in automotive, EV, or mobility products
  • Degree from a top computer science program
What we offer
  • Base salary of $200,000 – $240,000, plus equity
  • High ownership and direct impact at an early-stage company
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