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Founding Machine Learning Engineer Jobs in California

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$125 - $150/hr

Not Available Role Summary We are looking for a highly skilled Machine Learning Engineer / Research Engineer to join our founding team and help develop intelligent systems that transform how hardware ...

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 ...

Socket.dev

Machine Learning Engineer

Los Angeles, CA · On-site

$200 - $250/hr

Role Description Founding Data Scientist / Machine Learning Engineer We're looking for a highly ambitious Data Scientist to help build the predictive intelligence layer behind nowfluence. This is not ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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Founding Machine Learning Engineer information

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.

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 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.

Are founding machine learning engineers still in demand?

Founding machine learning engineers remain in high demand as companies seek to develop AI-driven products and services. They often require strong skills in deep learning, data modeling, and proficiency with tools like TensorFlow or PyTorch, with demand driven by growth in AI applications across industries.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $100,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses may also be part of the compensation package, especially in startup environments where they play a significant role in total earnings.

What are popular job titles related to Founding Machine Learning Engineer jobs in California?

For Founding Machine Learning Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Founding Machine Learning Engineer jobs in California look for?

The top searched job categories for Founding Machine Learning Engineer jobs in California are:

What cities in California are hiring for Founding Machine Learning Engineer jobs?

Cities in California with the most Founding Machine Learning Engineer job openings:

Founding Machine Learning Engineer jobs near you
Infographic showing various Founding Machine Learning Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Founding Machine Learning Engineer

Velvet

San Francisco, CA • On-site

Full-time

Re-posted 22 days ago

Job description

Job Summary:
Velvet is a data research company focused on creating high-quality audiovisual training data for AI. They are seeking a Founding Machine Learning Engineer to build pipelines that convert raw footage into structured training data, managing the full lifecycle from processing scripts to deployment at scale.
Responsibilities:
• Build and enhance post-processing pipelines that clean, validate, and package large volumes of video and audio data for multimodal model training.
• Deploy and fine-tune open-source models for speech recognition, speaker diarization, video segmentation, and related tasks.
• Design infrastructure for large-scale distributed processing — parallelizing thousands of compute jobs across cloud platforms and optimizing for throughput and cost.
Qualifications:
Required:
• Strong experience in ML infrastructure, speech/audio processing, or large-scale data pipelines.
• Proficiency in PyTorch.
• Familiarity with distributed job orchestration.
• Claude Code pilled.
• A bias toward shipping. You default to building, not theorizing.
• Ability to work effectively in an early-stage environment where scope is broad and priorities shift fast.
Preferred:
• Prior work at a data company or frontier AI lab.
• Track record building pipelines that process tens of thousands of hours of audio or video.
• Experience with infrastructure cost optimization or model fine-tuning for production use.
Company:
Infra and data for interactive AI. Founded in 2025, the company is headquartered in San Francisco, US, , with a team of 2-10 employees. The company is currently Early Stage.

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