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Physics Informed Machine Learning Jobs in Texas (NOW HIRING)

Koch Industries

Machine Learning Engineer

Austin, TX · On-site

$170K - $250K/yr

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 ...

New

Socket.dev

Data Scientist - Wireline

Houston, TX · On-site

$120 - $160/hr

... machine learning models and statistical algorithms * Automate data workflows and analysis using modern programming tools * Modeling & Technical Contributions * Build predictive and physics-informed ...

Weatherford

Data Scientist - Wireline

Houston, TX · On-site

... machine learning models and statistical algorithms * Automate data workflows and analysis using modern programming tools * Modeling & Technical Contributions * Build predictive and physics-informed ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... Physics, ect. ALTERNATE EXPERIENCE General comment on degrees: Most contracts allow additional ...

Vizient, Inc.

AVP, Machine Learning & Modeling

Irving, TX · On-site

$156K - $290K/yr

... drive data-informed decision-making across the enterprise. Oversee teams of data scientists ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

Vizient

AVP, Machine Learning & Modeling

Irving, TX

$156K - $290K/yr

... drive data-informed decision-making across the enterprise. Oversee teams of data scientists ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Photon

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

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Physics Informed Machine Learning information

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in Texas?

For Physics Informed Machine Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Texas look for?

The top searched job categories for Physics Informed Machine Learning jobs in Texas are:

What cities in Texas are hiring for Physics Informed Machine Learning jobs?

Cities in Texas with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Texas as of August 2026, with employment types broken down into 6% Internship, 46% Full Time, 42% Part Time, and 6% Contract. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Koch Industries

Austin, TX • On-site

$170K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New

Koch Industries rating

8.0

Company rating: 8.0 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

138th of 543 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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