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Physics Based Machine Learning Jobs in Pleasanton, CA

This position will be filled at either level based on knowledge and related experience as assessed ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

This position will be filled at either level based on knowledge and related experience as assessed ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

This position will be filled at eitherlevel based on knowledge and related experience as assessed ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

... of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex ...

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... We determine the base salary range for this role based on your primary work location: Mountain View ...

... of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex ...

Showing results 21-40

Physics Based Machine Learning information

See Pleasanton, CA salary details

$5

$22

$28

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

As of Aug 22, 2026, the average hourly pay for physics based machine learning in Pleasanton, CA is $22.33, according to ZipRecruiter salary data. Most workers in this role earn between $13.89 and $28.37 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 Pleasanton, CA look for?

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

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

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

Machine Learning Engineer (Technical Leadership)

Meta

Menlo Park, CA

$271K/yr

Full-time

Posted 5 days ago


Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 246 rated software companies


Job description

Meta is seeking a Machine Learning Engineer to join our integrity engineering team. The ideal candidate will have deep industry experience building and deploying machine learning systems at scale, including model development, training infrastructure, and optimization. You will work on leveraging ML models to detect and enforce content to keep the platforms safe and create a better user experience across Meta's products — from payment fraud detection and click-through rate prediction to search ranking, content enforcement, and spam detection. This role involves applying advanced ML techniques to some of the most exciting and massive-scale prediction problems on the web.
Machine Learning Engineer (Technical Leadership) Responsibilities:
  • Drive the team's ML strategy & technical direction to pursue opportunities that advance machine learning capabilities across the organization
  • Design and develop end-to-end machine learning systems, from data pipelines to model training, evaluation, and deployment
  • Lead experimentation and A/B testing frameworks to measure and optimize model performance
  • Build highly scalable classifiers and ML tools leveraging deep learning, data regression, and rules-based models
  • Adapt and optimize machine learning methods for modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
  • Partner with research teams to translate cutting-edge ML research into production systems
  • Mentor and influence ML engineers across organizations, raising the bar for ML best practices
  • Identify new ML opportunities for the larger organization and influence staffing/prioritization of these initiatives
  • Effectively communicate complex ML systems and architectural decisions to technical and non-technical stakeholders

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Experience leading projects with industry-wide impact
  • Experience communicating and working across functions to drive solutions
  • Experience in mentoring/influencing engineers across organizations
  • Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term vision
  • Experience in driving large cross-functional/industry-wide engineering efforts
  • 12+ years of experience in programming languages (Python, C++, or Java) with technical background
  • 8+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or deep learning based methods

Preferred Qualifications:
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Experience with deep learning frameworks (PyTorch, TensorFlow) and ML infrastructure tools
  • Familiarity with MLOps practices, model monitoring, and production ML systems
  • Experience building and optimizing large-scale model training pipelines
  • Experience shipping ML-powered products to millions of users or launching new ML product lines
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Publications or contributions to the ML research community

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$271,000/year to $347,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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