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Physics Based Machine Learning Jobs in Sausalito, CA

nudge

Machine Learning Engineer

San Francisco, CA · On-site

... based device that can stimulate and image the brain at high resolution and depth. This is a ... Strong first-principles understanding of engineering, physics, and signal processing. * Experience ...

Nudge

Machine Learning Engineer

San Francisco, CA · On-site

... based device that can stimulate and image the brain at high resolution and depth. This is a ... Strong first-principles understanding of engineering, physics, and signal processing. * Experience ...

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 · 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 ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift ... Must be based in the United States and possess valid work authorization. * Strong proficiency in ...

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$140 - $210/hr

... and LLM based planning and tool use, and translate it into practical enterprise solutions ... Deploy machine learning models into production systems, ensuring scalability and efficiency.

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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 23, 2026, the average hourly pay for physics based machine learning in Sausalito, CA is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $28.99 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 Sausalito, CA look for?

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

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

Cities near Sausalito, 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 Sausalito, CA as of August 2026, with employment types broken down into 72% Full Time, 16% Part Time, 6% Temporary, and 6% Contract. Highlights an 100% In-person job distribution, with an average salary of $47,470 per year, or $22.8 per hour.

Machine Learning Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$160K/yr

Full-time

Re-posted 6 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to "roll your own" and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
Responsibilities:
  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Use extensive experience to build, test, debug, and deploy production-grade components.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:
  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area
  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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