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Physics Based Machine Learning Jobs in Alameda, CA

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

PhD in Computer Science, Statistics, Mathematics, Physics, Operations Research, or related ... Our research-based data, analytics and indexes, supported by advanced technology, set standards for ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

PhD in Computer Science, Statistics, Mathematics, Physics, Operations Research, or related ... Our research-based data, analytics and indexes, supported by advanced technology, set standards for ...

MSCI

Machine Learning Researcher

San Francisco, CA

$144K - $187K/yr

PhD in Computer Science, Statistics, Mathematics, Physics, Operations Research, or related ... Our research-based data, analytics and indexes, supported by advanced technology, set standards for ...

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Physics Based Machine Learning information

See Alameda, CA salary details

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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 Alameda, CA is $22.74, according to ZipRecruiter salary data. Most workers in this role earn between $14.18 and $28.89 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 Alameda, CA? For Physics Based Machine Learning jobs in Alameda, CA, the most frequently searched job titles are:
What cities near Alameda, CA are hiring for Physics Based Machine Learning jobs? Cities near Alameda, CA with the most Physics Based Machine Learning job openings:
Physics Based Machine Learning jobs near you
Infographic showing various Physics Based Machine Learning job openings in Alameda, CA as of August 2026, with employment types broken down into 73% Full Time, 15% Part Time, 6% Temporary, and 6% Contract. Highlights an 100% In-person job distribution, with an average salary of $47,296 per year, or $22.7 per hour.

Principal Machine Learning Engineer, Embodied AI and Smart NPCs

Roblox

San Mateo, CA • On-site

Full-time

Re-posted 22 days ago

Job description

As a Principal Machine Learning Engineer within the Creator Services Machine Intelligence team, you will focus on the research and development of Embodied AI and Behavioral Agents that revolutionize how games are created and played on Roblox. You will bridge the gap between cutting-edge research and massive-scale product application, building agents capable of complex 3D gameplay and unblocking many use cases across Roblox, from automated playtesting to ensure quality, to "ML Players" with human-like movement and strategic reasoning, playing with real players in games.
You will work on feature extraction, model training, building validation / RL platform as well as inference set up leveraging methods from imitation learning to reinforcement learning. And you will create generalizable agents that can perceive 3D environments, understand game rules, plan long-term strategies, and execute complex physics-based actions in real-time.
You Will:
  • Design and implement foundation models end to end through the feature extraction to inference for embodied agents.
  • Define the long-term roadmap for Game AI and Embodied Intelligence, acting as a technical bar-raiser for code quality and architectural design.
  • Balance the exploration of cutting-edge deep learning research with the practical constraints of serving models to millions of concurrent users.
  • Mentor fellow engineers and researchers, fostering a culture of technical excellence and scientific inquiry.
  • Collaborate with Product Managers, Backend and Game Engine Engineers and other Roblox team members.
You Have:
  • PhD or Master's in Computer Science, Applied Math, or other field. A record of top-tier publications (e.g., NeurIPS, ICML, CVPR, AAAI, SIGGRAPH, etc) in embodied agents or related domains is a plus.
  • 7+ years of experience as a Machine Learning Engineer or Research Scientist, applying research to tangible products.
  • Deep technical understanding of Imitation Learning, Robotics, Reinforcement Learning, Computer Graphics and Vision, with experience working on low-latency motor control (human-like movement) and high-level strategic reasoning (game rules/goals).
  • Experience with building large scale data/feature pipeline, simulation environments for evaluation / RL.
  • Experience training models on large-scale distributed clusters and understanding the challenges of inference in real-time gaming environments.
  • Proficiency in Python (PyTorch/TensorFlow) and familiarity with C#, C++, or similar systems languages.
  • A passion for bridging the gap between research and production, moving beyond academic benchmarks to launch scalable solutions that directly impact millions of users.

Apply