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Physics Based Machine Learning Jobs in Mountain View, CA

Amat

Physics AI Scientist III

Santa Clara, CA · On-site +1

$142K - $196K/yr

Develop Scientific AI models that bridge scientific computing, physics-based simulation and machine learning for physics and chemistry-based engineering problems. * Design and train surrogate models ...

Applied Materials

Physics AI Scientist III

Santa Clara, CA · On-site

$142K - $196K/yr

Develop Scientific AI models that bridge scientific computing, physics-based simulation and machine learning for physics and chemistry-based engineering problems. * Design and train surrogate models ...

LLNL

Machine Learning Researcher

Livermore, CA · On-site

Experience in working with subject matter experts in one or more areas, such as physics, biology ... An employee's position within the salary range will be based on several factors including, but not ...

New

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 ...

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

As of Aug 20, 2026, the average hourly pay for physics based machine learning in Mountain View, CA is $23.67, according to ZipRecruiter salary data. Most workers in this role earn between $14.76 and $30.05 per hour, depending on experience, location, and employer.

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 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 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 job categories do people searching Physics Based Machine Learning jobs in Mountain View, CA look for?

The top searched job categories for Physics Based Machine Learning jobs in Mountain View, CA are:

What cities near Mountain View, CA are hiring for Physics Based Machine Learning jobs?

Cities near Mountain View, CA with the most Physics Based Machine Learning job openings:

Physics Based Machine Learning jobs near you

Scientist, Machine Learning

Atomic AI

South San Francisco, CA • On-site

$170K - $220K/yr

Full-time

Re-posted 23 days ago

Job description

At Atomic AI, we build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.

The opportunity

As a full-time Scientist on the Machine Learning team, you will work closely with engineers and experimental scientists to advance our technology platform for RNA structure prediction, target identification, and early drug discovery. You will co-lead the development and evaluation of the machine learning pipeline. You will contribute new ideas and realize their potential as part of a continuously advancing state-of-the-art platform. You will proactively shape the directions of the machine learning efforts and those of the whole company. 

Primary responsibilities

  • Design and develop novel machine learning models for RNA structure prediction and drug targeting.
  • Evaluate and advance the state of the art of our structure prediction platform.
  • Collaborate with our wetlab team on the targeted acquisition of experimental data to improve our machine learning models.
  • Develop high-quality code in a team setting.
  • Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
  • Work within a collaborative, high-caliber, interdisciplinary team and proactively shape the scientific and strategic vision of the company.

About you

  • Ph.D., M.Sc., or M.Eng. in Computer Science, Physics, Applied Mathematics, Materials Science, Computational Biology, or related field.
  • 4+ years of experience developing machine learning methods for scientific applications.
  • Foundational knowledge of machine learning and underlying mathematical concepts.
  • Proficiency in Python and deep learning frameworks (e.g., JAX, PyTorch).
  • Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.

Pluses

  • Publications at major machine learning conferences or in major scientific journal
  • Research experience related to structural biology, molecular design, and drug discovery.
  • Foundational knowledge of physics, chemistry, and molecular biology.
  • Demonstrated ability to develop performant code.

Salary Range (all levels): $170,000/year to $220,000/year + equity + benefits. This range reflects variations in seniority, expertise, and skills.

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About Atomic AI

Sourced by ZipRecruiter

Industry

Biotechnology research and development

Company size

11 - 50 Employees

Headquarters location

South San Francisco, CA, US

Year founded

2021

Social media

Twitter

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