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Machine Learning Startup Jobs in California (NOW HIRING)

Goodfire

Machine Learning Engineer

San Francisco, CA

$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 ...

Adobe

Senior Applied Scientist

San Jose, CA

$107K - $146K/yr

MS or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent ... startup inside the company whose products every brand on Earth already uses. About Adobe Adobe ...

Hum AI

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Senior Machine Learning Engineer Location: San Francisco About Hum.ai Hum.ai is building planetary ... Hum is a seed-funded startup on a mission to create positive impact through earth observation and ...

Adobe, Inc.

Machine Learning Engineer 5

San Jose, CA · On-site

Machine Learning Engineer - Brand Intelligence Predict The Opportunity Join us at Adobe as a ... startup inside the company whose products every brand on Earth already uses. About Adobe Adobe ...

Adobe, Inc.

Machine Learning Engineer 5

San Jose, CA · On-site

Machine Learning Engineer - Brand Intelligence Predict The Opportunity Join us at Adobe as a ... startup inside the company whose products every brand on Earth already uses. About Adobe Adobe ...

Adobe

Machine Learning Engineer 5

San Jose, CA

Machine Learning Engineer - Brand Intelligence Predict The Opportunity Join us at Adobe as a ... startup inside the company whose products every brand on Earth already uses. About Adobe Adobe ...

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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 Jul 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 are the key skills and qualifications needed to thrive in the Machine Learning Startup position, 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 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 is a Machine Learning Startup job?

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 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 July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 2% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $42,026 per year, or $20.2 per hour.

Machine Learning Engineer - Robot Manipulation

Maven Robotics

San Francisco, CA • On-site

Other

Re-posted 9 days ago

Job description

Company Overview

Maven Robotics is building the world's leading general-purpose AI robots.

We are currently operating in stealth and are growing the world's best team in AI robotics. We are looking for self-starters that are the world's best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.

Role Description

We are looking to recruit an exceptional Machine Learning Engineer - Robot Manipulation to design, implement, test, and deploy robot manipulation algorithms that enable assembly and material movement tasks.

In this role you will:

  • Design and implement machine learning algorithms, with a focus on reinforcement learning (RL) and imitation learning (IL), to enable robotic manipulators to perform complex tasks in dynamic environments.
  • Translate high-level objectives into machine learning problems and deploy robust, scalable models to real-world robotic systems.
  • Integrate your ML solutions into existing robotics workflows, ensuring that models are performant in both simulated and real-world settings.
  • Drive innovation by incorporating the latest research in machine learning into practical applications that push the boundaries of robotic manipulation.
  • Take ownership of critical ML projects, seeing them through from conception to successful deployment.
  • Collaborate across disciplines to ensure seamless integration of ML models and provide technical mentorship to junior engineers.
Qualifications

Must-have:

  • MS or PhD in machine learning, computer science, robotics, or a related field.
  • Strong practical experience in training and deploying machine learning models for real-world applications.
  • Deep understanding of reinforcement learning (RL) and imitation learning (IL) and their application to robotics.
  • Proficiency in programming languages and tools commonly used in machine learning (e.g., Python, PyTorch).
  • Experience with data collection, preprocessing, and management in the context of training ML models.
  • Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
  • Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:

  • Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
  • Experience in:
    • Designing and implementing reward functions for complex manipulation tasks.
    • Developing models that can handle noisy, incomplete, or sparse data.
    • Deployment of ML models to edge devices for real-time inference.
    • Accelerating ML training processes using GPU, TPU, or other HW accelerators.
    • Using reinforcement learning frameworks, e.g. Stable Baselines, RLlib, or similar.
  • General knowledge of robotics principles, including kinematics, dynamics, and control.
  • Publications or contributions to the machine learning community, particularly in areas related to robotics or reinforcement learning.

Apply