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Founding Machine Learning Engineer Jobs in Sunnyvale, CA

Known

AI / ML Engineer

San Francisco, CA · On-site

$200K - $375K/yr

Known - Founding Machine Learning Engineer * San Francisco, CA (In-Person) * 200k-375k Cash + Equity Known is a matchmaker that talks to users and supports them like a friend. Our mission is to ...

Known, Inc

AI / ML Engineer

San Francisco, CA · On-site

Known - Founding Machine Learning Engineer * San Francisco, CA (In-Person) * 200k-375k Cash + Equity Known is a matchmaker that talks to users and supports them like a friend. Our mission is to ...

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$37K

$151.1K

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How much do founding machine learning engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for founding machine learning engineer in Sunnyvale, CA is $151,130.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $181,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Founding Machine Learning Engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.
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Founding Machine Learning Engineer jobs near you

Founding Machine Learning Engineer

S23 Recruitment

San Francisco, CA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

S23 - AI
Founding Machine Learning Engineer
Location: San Francisco, CA (Onsite, 5 days per week)
Salary: $200,000 - $375,000 + Equity
About the Role
A fast-growing consumer AI company is looking to hire a Founding Machine Learning Engineer to help build the intelligence layer behind its next generation recommendation and matchmaking platform. The company has already raised significant seed funding, built strong early traction, and is scaling rapidly ahead of a planned Series A raise later this year.
This is a genuinely high impact role inside a small, elite engineering team, working directly alongside senior machine learning leadership from companies including Uber Eats, Faire, and Airbnb.
The focus is not generic AI tooling or internal automation. The work centres around recommendation systems, personalization, conversational AI, and deploying production machine learning systems that directly influence user outcomes at scale.
Key Responsibilities
  • Design, train, and deploy production machine learning models end to end
  • Build recommendation and personalization systems for consumer users
  • Develop evaluation frameworks and model monitoring systems
  • Work across structured, unstructured, and multimodal datasets
  • Contribute to conversational AI and agentic AI functionality
  • Collaborate closely with product and engineering teams in a highly iterative environment
  • Help shape the long term ML architecture and technical direction of the business
  • Operate inside a fast-moving startup environment with significant ownership
What We're Looking For
  • 4-8 years experience building and deploying ML systems in production
  • Strong recommendation systems or personalization experience within consumer products
  • Previous experience at consumer platforms, marketplaces, or matching-based products
  • Strong Python skills alongside modern ML frameworks such as PyTorch or TensorFlow
  • Experience deploying and monitoring models in production environments
  • Comfortable working in early stage or high growth startup environments
  • Strong understanding of end-to-end ML lifecycle and production systems
  • Ability to work onsite in San Francisco 5 days per week
Ideal Backgrounds
Candidates from companies such as Uber, Airbnb, DoorDash, Lyft, Tinder, Bumble, Zillow, Waymo, Cruise, Nuro, or similar consumer AI environments are particularly relevant.
Why Join?
  • Founding level opportunity with meaningful ownership and influence
  • Work directly with highly respected ML leadership
  • Strong compensation package with significant equity upside
  • Consumer AI company already showing strong market traction
  • Opportunity to build large-scale real world AI systems from an early stage
  • High impact environment with direct exposure to company growth and product direction

Apply