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Machine Learning Research Engineer Jobs in California

Erth.AI Inc.

Research Engineer

San Francisco, CA · On-site

$120K - $200K/yr

We are actively seeking a Research Engineer specializing in Machine Learning and AI to play a pivotal role in pioneering advanced solutions. In this role, you will lead end-to-end research projects ...

Rivet Industries

Machine Learning Researcher

San Jose, CA · On-site

$150K - $290K/yr

... Research Engineer to advance our computer vision and sensor fusion capabilities. This role combines cutting-edge research with practical implementation of machine learning pipelines for imaging, pose ...

Erth.AI Inc.

Research Engineer

San Francisco, CA

$120K - $200K/yr

We are actively seeking a Research Engineer specializing in Machine Learning and AI to play a pivotal role in pioneering advanced solutions. In this role, you will lead end-to-end research projects ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

The Camera & Depth Architecture organization is responsible for research, design, and ... As part of our machine learning team, you will play a vital role in prototyping foundational ...

UnifyID

Machine Learning Engineer

Redwood City, CA · On-site

The role involves designing, building, and deploying machine learning solutions while collaborating with a team of software engineers and researchers to tackle significant security challenges.

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All JobsMachine Learning Research Engineer JobsMachine Learning Research Engineer Jobs in California

Machine Learning Research Engineer information

See California salary details

$36.5K

$104.6K

$140.6K

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

As of Jun 8, 2026, the average yearly pay for machine learning research engineer in California is $104,624.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,600.00 and $102,600.00 per year, depending on experience, location, and employer.

What does a Machine Learning Research Engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are some common challenges faced by Machine Learning Research Engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

What are the key skills and qualifications needed to thrive in the Machine Learning Research Engineer position, and why are they important?

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What are popular job titles related to Machine Learning Research Engineer jobs in California? For Machine Learning Research Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Research Engineer jobs in California look for? The top searched job categories for Machine Learning Research Engineer jobs in California are:
Machine Learning Research Engineer jobs near you
Infographic showing various Machine Learning Research Engineer job openings in California as of May 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $104,624 per year, or $50.3 per hour.

Research Engineer

Erth.AI Inc.

San Francisco, CA • On-site

$120K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 4 days ago

Job description

We are actively seeking a Research Engineer specializing in Machine Learning and AI to play a pivotal role in pioneering advanced solutions. In this role, you will lead end-to-end research projects and contribute technical expertise to build scalable systems, all within the innovative landscape of generative media applications.
Company Introduction:
.Erth is an incubation studio with a dynamic platform empowering creators, encouraging self-expression, and enabling users to take ownership of their creations. Founded by seasoned industry veterans and serial entrepreneurs with expertise from Zynga, Facebook, Microsoft, Marvel, PlayStudios, and Big Fish Games. While our core team is primarily in San Francisco and New York City, we are open to qualified San Francisco/Bay Area hybrid candidates who thrive in a collaborative and evolving environment.
Job Responsibilities:
  • Lead and manage end-to-end machine learning research projects, ensuring alignment with strategic business goals from conceptualization to deployment.
  • Design, and develop machine learning systems.
  • Create advanced machine learning algorithms using frameworks like JAX, PyTorch, and TensorFlow, particularly for generative media applications.
  • Collaborate with cross-disciplinary teams to apply machine learning insights and enhance product offerings.
  • Utilize rigorous testing and iterative improvement processes to optimize the performance and accuracy of machine learning models.
  • Stay abreast of the latest AI research trends and technologies to guide and innovate future projects.

Requirements:
  • Minimum of 3-5 years of hands-on experience in machine learning model development, with expertise in JAX, PyTorch, and TensorFlow.
  • Demonstrated capability to independently lead research projects with end-to-end responsibility.
  • Deep understanding of ML and AI, focusing on building scalable solutions for large-scale data processing and model training.
  • Experience with low-level optimizations, such as CUDA kernel programming, is highly regarded but not mandatory.
  • Strong problem-solving skills and the ability to collaborate effectively within a multidisciplinary team environment.
  • Candidates must either possess a Ph.D. or be actively pursuing one

Nice to have:
  • Experience with LLMs and imaginative generative AI.
  • Participation in research projects/papers, especially if cited in the field of generative AI and/or ML.

Other Information:
Successful candidates for this position can expect a competitive salary within the range of $120,000 to $200,000, commensurate with experience and qualifications. In addition to a competitive salary structure, we offer a comprehensive benefits package, including health, dental, and vision coverage.
Employees will have the opportunity to participate in the CalSavers retirement program, contributing to their long-term financial well-being. Additionally, our organization recognizes the importance of work-life balance and provides generous perks such as unlimited Paid Time Off (PTO), ensuring our team members can recharge and maintain a healthy work-life equilibrium.
Please note that this role will require occasional in-office work in the San Francisco/Bay Area. We believe in fostering collaboration and connection among our team members, and periodic in-person engagement contributes to the overall success of our projects. We appreciate your understanding and flexibility in this regard. Join us in our journey to create a fulfilling and rewarding professional experience.

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