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Physics Based Machine Learning Jobs in Sunnyvale, CA

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$146K - $222K/yr

We have an opening for Machine Learning Research experts to join our team and advance the ... physics-constrained ML, or graph-based learning as demonstrated in software artifacts or ...

Apple Inc.

Machine Learning FEA Engineer

San Francisco, CA · On-site

$150.40 - $277.60/hr

... based on predictive finite element simulations and important design load cases. The machine ... Knowledges of Finite Element Analysis and/or other numerical methods in computational physics and ...

Apple

Machine Learning Engineer- GenAI

Cupertino, CA · On-site

... Research, Physics, Mechanical Engineering, Electrical Engineering or related field. Preferred ... Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their ...

Amat

Algorithm Developer III

Santa Clara, CA · On-site +1

$161K - $221K/yr

Develop predictive and control algorithms using a combination of traditional physics-based methods and machine learning approaches. * Build robust, maintainable software modules that integrate ...

Applied Materials

Algorithm Developer III

Santa Clara, CA · On-site

$161K - $221K/yr

Develop predictive and control algorithms using a combination of traditional physics-based methods and machine learning approaches. * Build robust, maintainable software modules that integrate ...

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Physics Based Machine Learning information

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How much do physics based machine learning jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for physics based machine learning in Sunnyvale, CA is $23.55, according to ZipRecruiter salary data. Most workers in this role earn between $14.66 and $29.90 per hour, depending on experience, location, and employer.

What does a physics based machine learning professional do?

Physics Based Machine Learning professionals often work on projects that involve applying machine learning techniques to physical systems, such as improving simulations in engineering, optimizing energy systems, or accelerating scientific research through data-driven modeling. Daily tasks might include developing algorithms that incorporate physical laws, analyzing simulation data, and collaborating with experts from engineering, data science, or research teams. The role can involve both theoretical and hands-on work, often requiring iterative testing and validation. This environment provides opportunities to tackle cutting-edge challenges, contribute to innovation, and potentially lead to career paths in research, product development, or advanced analytics.

What is a physics based machine learning?

A Physics Based Machine Learning job involves developing machine learning models that incorporate physical laws and domain knowledge to improve predictions and interpretability. Professionals in this field work at the intersection of physics, data science, and artificial intelligence to create models that are more robust, generalizable, and efficient, especially in scientific and engineering applications. Responsibilities often include data analysis, algorithm development, numerical simulations, and integrating physics-based constraints into ML models. These roles are common in industries like climate science, robotics, materials science, and computational physics.

What are the key skills and qualifications needed to thrive in physics based machine learning?

To thrive in Physics Based Machine Learning, you need advanced knowledge of physics, strong programming skills (Python, MATLAB, or C++), and a deep understanding of machine learning and statistical modeling, typically supported by a master's or PhD in physics, engineering, or a related field. Familiarity with simulation software, scientific computing libraries (such as TensorFlow, PyTorch, NumPy), and version control systems is essential. Strong problem-solving ability, effective communication, and cross-disciplinary collaboration skills set outstanding candidates apart. These competencies are crucial for designing robust, real-world models that integrate physical principles with data-driven techniques to solve complex problems.

What are popular job titles related to Physics Based Machine Learning jobs in Sunnyvale, CA? For Physics Based Machine Learning jobs in Sunnyvale, CA, the most frequently searched job titles are:
What cities near Sunnyvale, CA are hiring for Physics Based Machine Learning jobs? Cities near Sunnyvale, CA with the most Physics Based Machine Learning job openings:
Physics Based Machine Learning jobs near you

Staff Machine Learning Engineer, AI Infrastructure

Tesla

Palo Alto, CA • On-site

Full-time

Re-posted 25 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 681 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is seeking a Staff Machine Learning Engineer for its Bottle Rocket team to develop innovative, data-driven solutions on Tesla’s generative AI platform. The role involves leveraging machine learning models and deep learning techniques to solve complex problems, collaborating with cross-functional teams, and translating research concepts into scalable data products.
Responsibilities:
• Design, develop, train, and deploy machine learning solutions that leverage generative AI technologies, such as Large Language Models (LLMs)
• Analyze and improve the accuracy, efficiency, and scalability of AI models through rigorous data-driven experimentation, evaluation, and iterative model training processes
• Work closely with software engineers to productionize machine learning models and integrate them into scalable, reliable systems
• Optimize data pipelines and workflows to enable high-performance AI applications, leveraging specialized hardware when appropriate
• Deliver robust, high-impact data products that inform decision-making and enhance the capabilities of the generative AI platform
• Conduct research and remain up-to-date on the latest developments in AI/ML, with a special focus on generative AI, to rapidly test and prototype new ideas
• Convert complex business requirements and research findings into actionable insights and data-driven solutions
Qualifications:
Required:
• Proven experience in applying machine learning and AI techniques to solve real-world problems, particularly with generative AI and LLMs
• Strong proficiency with Python-based machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, JAX, TGI/vLLM, NumPy)
• Demonstrated ability to take research prototypes and deploy them as scalable, production-grade systems
• Expertise in working with and optimizing large datasets, data pipelines, and AI models
• Experience building robust, reliable solutions that minimize downtime and maximize user impact
• A problem-solving mindset, with strong attention to detail and a true follower of Occam's razor when designing and implementing solutions
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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