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Machine Learning Startup Jobs in California (NOW HIRING)

Spotter

Machine Learning Scientist

Culver City, CA · On-site

... Machine Learning Scientist with deep expertise in building and deploying production machine ... You thrive in a fast-paced startup environment and are motivated by building models that don't just ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have ... We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on ...

Nextdoor

Machine Learning Engineer - Ads

Bodega Bay, CA · On-site

$205K - $355K/yr

Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the ... Ability to succeed in a dynamic startup environment Rewards Compensation, benefits, perks, and ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $400K/yr

About the role We're looking for Machine Learning Engineers to help build our platform for training ... Startup or frontier lab experience in fast-moving teams. Our values Goodfire is looking for ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $400K/yr

About the role We're looking for Machine Learning Engineers to help build our platform for training ... Startup or frontier lab experience in fast-moving teams. Our values Goodfire is looking for ...

Clay Labs

Machine Learning Engineer

San Francisco, CA · On-site

$170K - $300K/yr

Machine Learning Engineer @ Clay Clay's ambition is to build a self-learning revenue engine : a ... startup environments Why Clay This is a rare greenfield: the Learning Team is new, its charter ...

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All JobsMachine Learning Startup JobsMachine Learning Startup Jobs in California

Machine Learning Startup information

See California salary details

$25.2K

$42K

$86.8K

How much do machine learning startup jobs pay per year?

As of Sep 11, 2026, the average yearly pay for machine learning startup in California is $42,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

What is a machine learning startup?

A Machine Learning Startup job typically involves working in a fast-paced, early-stage company focused on developing and applying machine learning technologies. Employees may take on diverse responsibilities, including data collection, model development, algorithm optimization, and deployment. Since startups require adaptability, roles often blend research, engineering, and business-oriented problem-solving. These positions offer opportunities to work on cutting-edge innovations but may also demand long hours and rapid prototyping.

What are the typical responsibilities and daily challenges when working at a machine learning startup?

At a Machine Learning Startup, your daily tasks often include collecting and preprocessing data, training and validating models, collaborating with engineers to deploy solutions, and iterating rapidly based on feedback and performance metrics. You may also contribute to brainstorming sessions, product roadmapping, and customer discovery processes. Common challenges include working with limited labeled data, balancing research with production needs, and managing shifting priorities as the business pivots or scales. This dynamic environment provides a valuable opportunity to make a tangible impact, develop a broad skill set, and gain exposure to multiple aspects of both technology and entrepreneurship.

What are the key skills and qualifications needed to thrive in a machine learning startup, and why are they important?

To succeed in a Machine Learning Startup, a strong background in computer science, statistics, and applied mathematics is essential, along with practical experience building and deploying machine learning models. Proficiency in tools such as Python, TensorFlow, PyTorch, and cloud-based platforms, as well as familiarity with data versioning and model deployment systems, is highly valuable. Adaptability, entrepreneurial thinking, and strong communication skills are crucial for thriving in the dynamic startup environment. These competencies enable effective product development, rapid iteration, and impactful collaboration within a fast-paced, resource-constrained setting.

What are the most commonly searched types of Machine Learning Startup jobs in California?

The most popular types of Machine Learning Startup jobs in California are:

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

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

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

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

What cities in California are hiring for Machine Learning Startup jobs?

Cities in California with the most Machine Learning Startup job openings:

Machine Learning Startup jobs near you
Infographic showing various Machine Learning Startup job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,026 per year, or $20.2 per hour.

Mid-Level Machine Learning Engineer

San Jose, CA • On-site

TetraMem - Accelerate The World
Computer and Peripheral Equipment Manufacturing • 11 - 50 employees
Learn more about TetraMem - Accelerate The Worldexternal

Full-time

Re-posted 26 days ago

Job description

Job Summary:
TetraMem is a company focused on accelerating the world through innovative technology, and they are seeking a Mid-Level Machine Learning Engineer to develop and optimize machine learning models for edge AI applications. The role involves collaborating with hardware and software teams, providing mentorship, and researching state-of-the-art ML techniques to enhance model efficiency.
Responsibilities:
• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Work closely with hardware and software teams to integrate ML models into production systems.
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
• Provide technical leadership and mentorship to junior engineers.
• Publish research findings, present at conferences, and contribute to open-source projects when applicable.
Qualifications:
Required:
• 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
• Strong experience in machine learning, with a focus on edge AI and lightweight model deployment.
• Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.
• Proficiency in programming languages such as C/C++, Python, and experience with ML model optimization.
• Ability to work independently and collaboratively in a fast-paced startup environment.
• Ability to provide mentorship, technical guidance, and career development support to junior engineers and interns.
Preferred:
• Understanding of ML compiler and runtime design.
• Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
• Familiarity with hardware acceleration techniques.
• Experience in embedded system development.
Company:
TetraMem is developing cutting-edge analog computing solutions for AI applications, offering exceptional performance with ultra-low power consumption. Founded in 2018, the company is headquartered in Newark, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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