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Physics Informed Neural Networks Jobs in Austin, TX

Machine Learning Engineer

Austin, TX · On-site

$170K - $250K/yr

Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series). * Incorporate physics-informed constraints so ...

Posted today

S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ... Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest * Distributed computing tools and ...

S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ... Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest * Distributed computing tools and ...

... neural networks. * Prior experience working with AWS is a plus. * Some experience with natural ... Mathematics, Statistics, CS, Physics, MIS, Economics, Electrical Engineering, etc. * 2+ years ...

Physics Informed Neural Networks information

See Austin, TX salary details

$5

$19

$25

How much do physics informed neural networks jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for physics informed neural networks in Austin, TX is $19.89, according to ZipRecruiter salary data. Most workers in this role earn between $12.40 and $25.24 per hour, depending on experience, location, and employer.

What is a physics informed neural network?

A Physics Informed Neural Networks (PINNs) job typically involves developing and applying neural networks that incorporate physical laws as constraints to solve complex scientific and engineering problems. Professionals in this field work on integrating differential equations into deep learning models to improve predictions and reduce the need for large training datasets. These roles are common in fields like fluid dynamics, material science, and climate modeling, where traditional computational methods can be expensive. Individuals in this role often have expertise in machine learning, numerical methods, and domain-specific physics.

What does a physics informed neural network do?

In a Physics Informed Neural Networks role, your daily tasks will often include designing, building, and testing neural network architectures that incorporate physical laws and constraints. You will frequently collaborate with domain experts, such as physicists or engineers, to integrate scientific knowledge into machine learning models and validate the results with real-world data. Regular responsibilities also involve coding, running experiments, analyzing results, and documenting findings for presentation or publication. This collaborative and research-driven environment helps ensure that models are both accurate and physically consistent, and offers opportunities for interdisciplinary learning and skill advancement.

What are the key skills and qualifications needed to thrive in physics informed neural networks?

To thrive in Physics Informed Neural Networks (PINNs), you need a strong background in physics, mathematics, and deep learning frameworks, typically evidenced by advanced degrees in physics, applied mathematics, computer science, or engineering. Experience with programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch, as well as experience in numerical simulation tools, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in multidisciplinary teams. These qualifications and soft skills are essential for developing accurate, interpretable models that integrate scientific knowledge with machine learning to solve complex real-world problems.

What cities near Austin, TX are hiring for Physics Informed Neural Networks jobs?

Cities near Austin, TX with the most Physics Informed Neural Networks job openings:

Infographic showing various Physics Informed Neural Networks job openings in Austin, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $41,364 per year, or $19.9 per hour.

Machine Learning Engineer

Koch Industries

Austin, TX • On-site

$170K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 hours ago

Posted today


Koch Industries rating

8.0

Company rating: 8.0 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

136th of 540 rated manufacturers


Job description

Your Job
The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle.
Our Team
Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast.
What You Will Do
  • Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series).
  • Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit.
  • Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive.
  • Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis.
  • Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning.

Who You Are (Basic Qualifications)
  • Extensive hands-on experience building, training, and deploying ML models in production - not just using pretrained APIs.
  • 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML).
  • Strong Python with PyTorch or TensorFlow.
  • Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain.
  • Experience with Azure Machine Learning or a similar cloud ML platform.
  • Familiarity with uncertainty quantification (Bayesian approaches, ensembling).

What Will Put You Ahead
  • Direct experience with industry-standard EM or physics simulation tools.
  • Geometric deep learning (graph neural networks, mesh-based models) for CAD data.
  • Background in RF/high-speed electronics or interconnect design.

For this role, we anticipate paying $170,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.
At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.
Hiring Philosophy
All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here .
Who We Are
As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before.
At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company.
Our Benefits
Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter.
Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.
Equal Opportunities
Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here , aquí , or tu ).

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