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Nvidia Machine Learning Jobs in Berkeley, CA (NOW HIRING)

Zensors

AI/ML Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

As a Machine Learning Engineer in ML Runtime & Optimization , you will develop technologies to ... Working across the entire ML framework/compiler stack (e.g., PyTorch, CUDA, TensorRT, and NVIDIA ...

Hive

Data Center Technician

San Francisco, CA

$70K - $120K/yr

Our Hive machine learning systems run on our own data centers with hybrid emphases on high ... Experience with NVIDIA GPU linux software stack * Configuration Management - Chef * Version Control ...

Lambda

Field Engineering Intern - Summer 2026

San Francisco, CA · On-site

$19.75 - $25.50/hr

... NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove * We have research papers accepted at top machine learning and graphics conferences ...

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All JobsNvidia Machine Learning JobsNvidia Machine Learning Jobs in Berkeley, CA

Nvidia Machine Learning information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

How much do nvidia machine learning jobs pay per year?

As of Jun 13, 2026, the average yearly pay for nvidia machine learning in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 per year, depending on experience, location, and employer.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

What is a Nvidia Machine Learning job?

A Nvidia Machine Learning job involves developing and optimizing AI models, deep learning frameworks, and GPU-accelerated applications. Engineers in this role work on cutting-edge research, building scalable ML solutions, and improving performance on Nvidia hardware like GPUs and AI accelerators. They collaborate with software and hardware teams to enhance AI capabilities across industries such as gaming, healthcare, and autonomous systems. Strong coding skills in Python, C++, and experience with ML frameworks like TensorFlow or PyTorch are often required.

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

To thrive in an Nvidia Machine Learning role, a deep understanding of machine learning algorithms, proficiency in programming languages like Python or C++, and a solid background in mathematics or computer science are essential. Experience with Nvidia's CUDA, TensorRT, cuDNN, and familiarity with modern deep learning frameworks such as TensorFlow or PyTorch are highly valued, as are relevant certifications in AI or data science. Strong problem-solving skills, teamwork, and effective communication distinguish top candidates in collaborative, fast-paced environments. These skills are crucial for developing and optimizing AI solutions that leverage Nvidia’s advanced hardware and software platforms.

Does NVIDIA do machine learning?

Nvidia offers extensive tools and platforms for machine learning, including GPUs optimized for training and deploying models. Many machine learning engineers and researchers use Nvidia hardware and software frameworks like CUDA and cuDNN to accelerate AI development. The company also provides training resources and certifications related to AI and deep learning.

What are some common challenges faced by professionals in Nvidia Machine Learning roles?

One common challenge in Nvidia Machine Learning roles is optimizing models to fully leverage GPU architectures for both performance and efficiency, which requires continuous learning as the technology rapidly evolves. Team members often work on complex, large-scale projects that demand close collaboration across software, hardware, and research divisions. Navigating the fast pace of innovation and contributing effectively to cross-functional teams is essential for success. However, these challenges also make the role exciting and offer excellent opportunities for professional growth and hands-on experience with state-of-the-art AI solutions.

Is ML a high paying job?

Machine Learning roles, including positions like Nvidia Machine Learning engineers, tend to offer high salaries due to the specialized skills required, such as programming, data analysis, and knowledge of AI frameworks. Compensation varies based on experience, location, and industry, but generally ranks above average compared to many other tech roles.

How difficult is it to get hired at NVIDIA?

Getting hired for a machine learning role at NVIDIA can be competitive, often requiring strong technical skills in deep learning, programming (such as Python and CUDA), and relevant experience or advanced degrees. The hiring process typically involves multiple interviews, technical assessments, and a review of project work or research contributions.
What job categories do people searching Nvidia Machine Learning jobs in Berkeley, CA look for? The top searched job categories for Nvidia Machine Learning jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Nvidia Machine Learning jobs? Cities near Berkeley, CA with the most Nvidia Machine Learning job openings:
Nvidia Machine Learning jobs near you
Infographic showing various Nvidia Machine Learning job openings in Berkeley, CA as of June 2026, with employment types broken down into 50% Full Time, 31% Part Time, 15% Contract, and 4% Nights. Highlights an 83% Physical, 8% Hybrid, and 9% Remote job distribution, with an average salary of $52,141 per year, or $25.1 per hour.
Deep Learning Engineer

Deep Learning Engineer

Blackstone Restaurant

San Francisco, CA • Hybrid

Other

Posted 3 days ago

Job description

Deep Learning Engineer

Blackstone Talent Group, an award-winning technology consulting and talent agency is seeking a Deep Learning Engineer to join our client's team.

As a Deep Learning Engineer at our client, you will make key contributions towards building foundational AI capabilities that will enable solving complex problems for their customers. In this role, you will build, train, evaluate and deploy state of the art ML models in production at scale. You will report into the Director of AI within the Perception Org and work closely with other engineering as well as product teams to deliver value to clients customers.

We are looking for someone who has familiarity with or growing expertise in at least one of the verticals below — depth in a specific area is valued but not required on day one.

  • 3D vision models to predict depth and 3D structure
  • Video/temporal behavior models to predict intent
  • Deep understanding of Vision language models and hands-on experience fine tuning them
  • Deep understanding of foundation models in perception
  • Deep knowledge of Nvidia edge device stack for running ML models and cuda know-how in terms delivering highly optimized models

This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.

Key Responsibilities

Below are your primary responsibilities. These represent the core areas where you'll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.

  • Come up with solutions to complex problems in perception using deep learning.
  • Articulate ideas both verbally and in written form culminating in clear design and project plan docs for their work
  • Contribute to team roadmap and planning
  • Work with cross functional teams across the company and contribute towards delivery of end to end solutions for the customer

Required Qualifications

The qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.

  • Experience: 1-2 years experience building and deploying machine learning models for perception in production settings.
  • Core Skills: Solid hands-on experience designing, training, and evaluating machine learning models for perception. Demonstrated ability to independently build ML pipelines and deploy models to cloud environments (AWS, GCP, or Azure); familiarity with MLOps practices including experiment tracking, model versioning, and automated workflows. Hands-on experience in PyTorch, Python, and related skills.
  • Personal Attributes: Good communicator, self starter and ability to collaborate with others, quick learner who can adapt to a fast paced startup culture
  • Education: Bachelors or Masters in Computer Science or related field
  • Nice to Have: Experience working in perception problems in self driving car companies that aligns closely with the work of this team.

Security Clearance Required: N/A Blackstone Talent Group is a wholly owned subsidiary of Blackstone Technology Group, a global IT services and software firm that implements technological solutions across commercial industry verticals and the US Federal Government. Blackstone's global talent augmentation practice was founded in 1998. Blackstone Talent Group has offices in San Francisco, Denver, Houston, Colorado Springs, and Washington, DC. We specialize in providing clients the best talent across a variety of industries and sectors. EOE of Minorities/Females/Veterans/Disabilities

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