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Physics Based Machine Learning Jobs in Alameda, CA

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 ...

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and ... Machine Learning Manager In order to execute our vision, we're constantly growing our machine ...

... 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 ...

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and ... Machine Learning Manager In order to execute our vision, we're constantly growing our machine ...

... 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 ...

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 ...

Machine Learning Engineer

San Francisco, 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 ...

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 ...

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

Showing results 41-60

Physics Based Machine Learning information

See Alameda, CA salary details

$5

$22

$28

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:
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.

Machine Learning Engineer

Advatix Inc.

San Mateo, CA • On-site

$110 - $165/hr

Other

Medical, Dental, Vision, PTO

Posted 5 days ago


Job description

Department: Information Technology, Type: Full Time

Job Title: Machine Learning Engineer / Research Engineer

Pay: $$110,000 – $165,000 Base Salary + Equity

Shift: N/A

Location: San Mateo, CA (Peninsula) – Onsite Preferred

Schedule: Full time, Permanent Role

Visa Sponsorship: Not Available

Relocation Assistance: Not Available

Role Summary

We are looking for a highly skilled Machine Learning Engineer / Research Engineer to join our founding team and help develop intelligent systems that transform how hardware and mechanical engineers design products. This is a unique opportunity to work at the intersection of cutting‑edge machine learning research and real‑world engineering applications. You'll collaborate directly with founders, engineers, and customers to design, train, deploy, and continuously improve machine learning systems that accelerate CAD workflows and hardware design. As one of the earliest ML hires, you will have significant ownership over technical direction, architecture decisions, and the long‑term evolution of our AI platform.

Key Responsibilities Machine Learning Research & Development
  • Design, train, and optimize custom deep learning models that understand CAD workflows and generate intelligent next‑step design recommendations.
  • Develop novel machine learning approaches for geometry, design, and engineering‑related datasets.
  • Evaluate emerging research in areas such as sequence modeling, geometric deep learning, representation learning, and foundation models.
Data & Model Infrastructure
  • Build and maintain scalable Python‑based training, evaluation, and experimentation pipelines.
  • Transform complex, real‑world CAD and geometry data into high‑quality training datasets and signals.
  • Implement robust offline and online evaluation frameworks to measure model performance and business impact.
Production ML Systems
  • Own the complete ML lifecycle from research and prototyping through deployment, monitoring, and optimization.
  • Architect model‑serving infrastructure and backend components that enable fast, reliable integration into CAD environments.
  • Establish best practices for experimentation, logging, model versioning, and performance monitoring.
Cross‑Functional Collaboration
  • Work closely with founders, mechanical engineers, hardware engineers, and early customers to understand workflows and translate them into ML solutions.
  • Collaborate with backend engineers on APIs, infrastructure, data models, and platform scalability.
  • Help define the long‑term strategy for applying machine learning to hardware and CAD design.
Skills & Qualifications Machine Learning Expertise
  • 4+ years of hands‑on machine learning experience in industry, research, or a combination of both.
  • Equivalent Master's or PhD research experience will be considered.
  • Demonstrated success designing, training, improving, and deploying machine learning models—not simply utilizing hosted AI APIs.
Deep Learning & Research
  • Expert‑level proficiency with PyTorch (preferred) or similar frameworks such as TensorFlow or JAX.
  • Experience implementing custom architectures, loss functions, optimization methods, and training loops.
  • Strong understanding of model evaluation, experimentation, and performance trade‑offs.
Software Engineering
  • Strong Python programming skills with experience building production‑ready systems.
  • Ability to write clean, maintainable, and well‑tested code with appropriate documentation and abstractions.
  • Experience developing scalable ML infrastructure and backend services.
Ownership & Execution
  • Proven ability to independently drive projects from concept through deployment.
  • Experience building end‑to‑end ML systems including data pipelines, experimentation frameworks, model training, deployment, and monitoring.
  • Comfortable solving ambiguous, open‑ended technical problems.
Communication & Collaboration
  • Excellent communication skills with the ability to explain technical concepts to both technical and non‑technical stakeholders.
  • Experience working cross‑functionally with engineers, product teams, researchers, and customers.
Startup Mindset
  • Thrives in fast‑paced, high‑ownership environments.
  • Comfortable wearing multiple hats across machine learning, research, backend engineering, and infrastructure.
Preferred Qualifications
  • Published research papers or meaningful open‑source contributions demonstrating novel technical work.
  • Experience with:
    • CAD systems and workflows
    • Computational geometry
    • Computer graphics
    • 3D representations
    • Robotics
    • Familiarity with cloud ML infrastructure (AWS, GCP).
    • Experience with backend frameworks such as FastAPI, Flask, or Django.
Must‑Have Requirements
  • Must be based in the United States and possess valid work authorization.
  • Strong proficiency in Python and modern deep learning frameworks (PyTorch preferred).
  • Demonstrated experience building and deploying custom machine learning models from scratch.
  • Experience designing architectures, creating training pipelines, and shipping ML features to production.
  • Minimum 4 years of relevant industry or equivalent academic experience.
Benefits & Perks
  • Competitive salary ($110,000 – $175,000)
  • Meaningful equity ownership
  • Comprehensive medical, dental, and vision insurance
  • Catered team lunches at the San Mateo office
  • Unlimited/flexible paid time off
  • High‑impact role within a YC‑backed startup
  • Direct collaboration with experienced founders and engineers
  • Significant opportunities for growth, learning, and career advancement
  • Opportunity to help define the future of AI‑powered CAD and hardware design

HRforGrowthis an extension of the Growth Catalyst Group (GCG), a partnership of companies with more than 65 years of operating experience and a history of successfully serving customers across industries and disciplines.

GCG® is one of the world’s leading providers of business transformation solutions related to supply chain and technology solutions for order fulfillment and marketing execution. We are committed to an inclusive workplace that does not discriminate against race, nationality, religion, age, marital status, physical or mental disability, sexual orientation, gender, orgender identity. We believe in diversity and encourage anyqualifiedindividual to apply. We are an EEOCEmployer.

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