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Physics Based Machine Learning Jobs (NOW HIRING)

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning ... The ideal candidate will possess hands-on experience with Azure Databricks, Python-based model ...

Celanese

Digital Innovation Engineer

Wilmington, DE · On-site

Proficiency in AI + physics-based machine learning. * Working understanding of material science fundamentals * Strong foundation in applied statistics, experimental design, and probabilistic modeling.

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

By enabling high-fidelity, multi-physics simulation through AI inference across the entire ... We have hybrid offices in London, New York, and Singapore; this role is remote based in the San ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

$147K - $272K/yr

Build differentiable simulation and physics-informed machine learning pipelines to analyze and improve cameras and sensors. Ground the exploration via validated simulation and metrology results to ...

Amat

Physicist/Scientist Machine Learning

Santa Clara, CA · On-site +1

$138K - $190K/yr

Focus will be on developing ML models based on plasma and electromagnetic simulations. This role is ... Experience with NVIDIA Physics NeMo , NVIDIA Modulus, or related physicsinformed or ...

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

As of Jun 5, 2026, the average hourly pay for physics based machine learning in the United States is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $25.48 per hour, depending on experience, location, and employer.

What types of projects or problems does a Physics Based Machine Learning professional typically work on?

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 job?

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 the Physics Based Machine Learning position, and why are they important?

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.

More about Physics Based Machine Learning jobs
What cities are hiring for Physics Based Machine Learning jobs? Cities with the most Physics Based Machine Learning job openings:
What states have the most Physics Based Machine Learning jobs? States with the most job openings for Physics Based Machine Learning jobs include:
What job categories do people searching Physics Based Machine Learning jobs look for? The top searched job categories for Physics Based Machine Learning jobs are:
Physics Based Machine Learning jobs near you
Infographic showing various Physics Based Machine Learning job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 61% Full Time, and 37% Part Time. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $41,731 per year, or $20.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

Compunnel

Plano, TX • On-site

Contractor

Posted 4 days ago

Job description

Job Summary
We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus on building ML-ready data architectures, developing scalable machine learning solutions, and supporting enterprise analytics initiatives. The ideal candidate will possess hands-on experience with Azure Databricks, Python-based model development, Medallion Architecture, and MLOps practices, along with the ability to collaborate effectively with business and technical stakeholders.
Key Responsibilities
  • Design, develop, and maintain machine learning solutions that support advanced analytics and predictive modeling initiatives.
  • Build and optimize ML-ready data pipelines and data architectures using Medallion Architecture principles.
  • Develop and manage data ingestion, transformation, and curation processes across Bronze, Silver, and Gold data layers.
  • Create scalable feature engineering workflows and production-grade machine learning assets.
  • Design and implement machine learning pipelines using Azure Databricks and related cloud technologies.
  • Leverage Delta Lake, MLflow, and workflow orchestration tools to operationalize machine learning models and data transformations.
  • Develop and maintain Python-based machine learning models, feature engineering processes, and MLOps automation solutions.
  • Build and optimize SQL transformations, views, and ELT pipelines to support analytics and machine learning workloads.
  • Design and maintain feature stores, semantic layers, and curated datasets that support enterprise reporting and machine learning initiatives.
  • Integrate machine learning outputs into analytics platforms, dashboards, and business intelligence solutions.
  • Collaborate with business stakeholders, technical teams, and leadership to translate business requirements into scalable data and machine learning solutions.
  • Establish engineering standards, best practices, and scalable development processes for machine learning and data engineering initiatives.
  • Monitor data quality, model performance, and operational effectiveness of machine learning solutions.

Required Qualifications
  • 5-7 years of hands-on experience in machine learning engineering and data engineering.
  • 10+ years of experience delivering enterprise-scale data, analytics, and machine learning solutions.
  • Strong experience building machine learning models and supporting model development using Python.
  • Extensive experience with Azure Databricks for machine learning, feature engineering, and data engineering workloads.
  • Deep understanding of Medallion Architecture, including Bronze, Silver, and Gold data layer design and implementation.
  • Experience designing ML-ready data architectures and scalable data engineering solutions.
  • Experience migrating workloads to Databricks and implementing modern data platform architectures.
  • Hands-on experience with Delta Lake, MLflow, and Databricks Workflows.
  • Strong proficiency in Python for model development, feature engineering, and MLOps automation.
  • Advanced SQL skills with experience building optimized transformations, views, and ELT pipelines.
  • Experience designing feature stores, semantic models, and machine learning-ready datasets.
  • Strong understanding of machine learning lifecycle management, data engineering best practices, and scalable architecture patterns.
  • Ability to lead technical initiatives and establish engineering standards and development practices.
  • Strong business acumen and ability to communicate effectively with technical and business stakeholders.
  • Experience working in collaborative, fast-paced environments that encourage experimentation and innovation.

Preferred Qualifications
  • Experience working within Microsoft Azure cloud environments.
  • Experience integrating machine learning outputs into analytics platforms and business intelligence solutions.
  • Experience designing dashboards and reporting solutions that surface machine learning insights, data quality metrics, and model performance indicators.
  • Familiarity with Power BI, including DAX, semantic modeling, and visualization best practices.
  • Experience supporting enterprise-scale analytics, data science, and AI initiatives.
  • Experience mentoring technical teams and providing technical leadership on machine learning and data engineering projects.
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About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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