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Machine Learning Postdoc Jobs in California (NOW HIRING)

LLNL

Explainable AI - Postdoctoral Researcher

Livermore, CA · On-site

$136K/yr

We have an opening for a Postdoctoral Researcher in Explainable AI to contribute to fundamental R&D ... Conduct cutting-edge machine learning research effectively and independently. * Actively ...

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Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive in a machine learning postdoc position?

To thrive as a Machine Learning Postdoc, you need a deep understanding of machine learning algorithms, statistical modeling, and research methodology, typically supported by a completed PhD in a related field. Proficiency with programming languages like Python or R, experience with ML libraries (e.g., TensorFlow or PyTorch), and familiarity with large-scale datasets and cloud computing platforms are important. Strong analytical thinking, effective communication, and the ability to collaborate across multidisciplinary teams are standout soft skills in this position. These qualifications ensure innovative research contributions, successful project execution, and effective dissemination of findings in both academic and applied settings.

What is a machine learning postdoc?

A Machine Learning Postdoc is a research-focused position typically held after earning a Ph.D. in a related field. It involves conducting advanced research in machine learning, developing new algorithms, and publishing in top-tier conferences and journals. Postdocs often collaborate with faculty, industry partners, and other researchers to advance the state of the art in AI. The role may include mentoring students and contributing to grant proposals. It serves as a bridge between doctoral studies and a long-term academic or industry research career.

What are the typical responsibilities and collaborative aspects of a machine learning postdoc?

A Machine Learning Postdoc typically conducts original research, develops and tests new algorithms, and contributes to academic publications or patent applications. Daily tasks often involve data analysis, model building, and experimentation using advanced computational tools. Collaboration is key in this role, as postdocs frequently work alongside faculty, graduate students, and external industry partners to advance research objectives. Additionally, they may mentor junior researchers or students, present at conferences, and participate in grant writing or project planning. This mix of independent research and team collaboration fosters both professional growth and impactful scientific advancements.

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

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

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

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

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Machine Learning Postdoc jobs near you
Infographic showing various Machine Learning Postdoc job openings in California as of August 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 96% In-person, and 4% Hybrid job distribution.

Postdoctoral Researcher, Real-Time Generative AI for Automotive XR

Toyota Research Institute

Los Altos, CA

$152K - $218K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago

Job description

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.


The Mission

Our team uses design thinking process to place the human at the center of determining the needs, design, and implementation of human-machine interfaces. By following this process, the HMIR team creates automotive HMI technologies that allow humans of any ability to work in harmony with AI.

The Team

In the Human-Machine Interaction Research group (HMIR), we design, develop and evaluate novel interfaces to improve the safety, well-being, and performance of drivers using human-centered artificial intelligence.

The Opportunity

We are seeking a Postdoctoral Researcher for a research project exploring next-generation extended reality (XR) experiences for vehicles. The project investigates how generative AI and real-time video processing can enable new forms of visual augmentation and interaction between drivers and their environment. This role is intended for a researcher who can take ownership of core technical directions, drive implementation and evaluation, and coordinate closely with collaborators to deliver high-quality research outcomes.

This year-long postdoctoral research position will be highly integrated into the Human-Machine Interaction Research (HMIR) team at TRI. Please note that this opportunity will be an in-office role based in Los Altos, CA, and includes multiple trips to test tracks.

Responsibilities
  • Ph.D. in Machine Learning, Computer Science, Electrical Engineering, or a related field.
  • Track record of publications in top-tier venues (e.g. CVPR, ICCV, NeurIPS, ICML, ICLR).
  • Strong foundation in machine learning, especially in computer vision.
  • Extensive hands-on experience with image/video generative models.
  • Strong programming skills in Python; experience with Linux-based development.
  • Proven ability to lead research projects to publication-quality outcomes.
Qualifications
  • Ph.D. in Machine Learning, Computer Science, Electrical Engineering, or a related field.
  • Track record of publications in top-tier venues (e.g. CVPR, ICCV, NeurIPS, ICML, ICLR).
  • Strong foundation in machine learning, especially in computer vision.
  • Extensive hands-on experience with image/video generative models.
  • Strong programming skills in Python; experience with Linux-based development.
  • Proven ability to lead research projects to publication-quality outcomes.
Bonus Qualifications
  • Experience in real-time or resource-constrained ML systems.
  • Experience with GPU acceleration, profiling, or low-level optimization.
The pay range for this position at commencement of employment is expected to be between $152,000 and $218,500/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.

Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
 
TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.
 
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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