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Physics Informed Neural Networks Jobs (NOW HIRING)

Snowflake

Staff Research Scientist, Exotic AI

Bellevue, WA · On-site

$236K - $339K/yr

Experience with latent dynamics modeling, model-based RL, or physics-informed neural networks (GraphCast, FourCastNet, AlphaFold-style architectures) * Contributions to open-source ML frameworks or ...

SpaceX

Sr. Software Engineer, Computer Vision

Hawthorne, CA · On-site

$160K - $225K/yr

Experience applying AI to physics or simulation domains, using physics-informed neural networks (PINNs) or surrogate modeling ADDITIONAL REQUIREMENTS: * Ability to work extended hours and weekends as ...

SpaceX

Sr. Software Engineer, Computer Vision

Hawthorne, CA · On-site

$160K - $225K/yr

Experience applying AI to physics or simulation domains, using physics-informed neural networks (PINNs) or surrogate modeling ADDITIONAL REQUIREMENTS: * Ability to work extended hours and weekends as ...

SpaceX

Sr. Software Engineer, Computer Vision

Hawthorne, CA · On-site

$160K - $225K/yr

Experience applying AI to physics or simulation domains, using physics-informed neural networks (PINNs) or surrogate modeling ADDITIONAL REQUIREMENTS: * Ability to work extended hours and weekends as ...

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

As of Jul 15, 2026, the average hourly pay for physics informed neural networks 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 is a Physics Informed Neural Networks job?

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 are the key skills and qualifications needed to thrive in the Physics Informed Neural Networks position, and why are they important?

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 are the typical daily tasks involved in a Physics Informed Neural Networks position?

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.

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Physics Informed Neural Networks jobs near you
Infographic showing various Physics Informed Neural Networks job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 14% Part Time, and 1% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $41,731 per year, or $20.1 per hour.

Research Scientist I/II, Multiscale & Multiphysics Simulations

Lila Sciences

Cambridge, MA • On-site

$176K - $304K/yr

Full-time

Medical, Dental, Vision, Life

Posted yesterday

Job description

Your Impact at LILA
Your role will focus on building next-generation in silico multiphysics and multiscale simulation capabilities that power AI-driven scientific discovery. You will develop high-fidelity digital representations of complex physical systems spanning chemical and mechanical processes, transport phenomena, and electromagnetic behavior and integrate them into autonomous discovery and experimental pipelines.
You will work on integrating simulation methods-such as finite element modeling, computational fluid dynamics, phase-field methods, and TCAD-style transport/process modeling-into scalable, programmatic, and agent-driven systems that enable real-time digital twins, simulation-informed decision-making, and autonomous closed-loop workflows
What You'll Be Building
  • Develop and deploy robust multiphysics models across coupled domains (e.g., thermal, fluid, structural, electromagnetic, chemical), using methods such as coarse-grained, mesoscale, FEM, and CFD techniques.
  • Build integrated multiscale frameworks that connect atomistic, mesoscale, and continuum representations to model materials and devices.
  • Design and implement programmatic, agent-driven simulation workflows that can autonomously configure, execute, and refine simulations within closed-loop discovery workflows.
  • Create scalable, GPU-accelerated simulation pipelines, data infrastructure, and interoperable APIs that connect commercial tools (e.g., COMSOL, ANSYS) and custom solvers deploying on cloud-based, high-throughput computing environments
  • Collaborate with AI, software, and automation teams to orchestrate and deploy closed-loop discovery workflows, integrating computational predictions with robotic and cloud-based laboratory platforms to enable automated experiment-simulation feedback cycles and accelerated R&D.

What You'll Need to Succeed
  • PhD in Mechanical Engineering, Chemical Engineering, Aerospace Engineering, Materials Science, or a related field.
  • Extensive experience with multiphysics simulation methods and numerical algorithms, including FEM, CFD, TCAD/process simulation, mesoscale modelling, or related techniques.
  • Strong foundation in coupled physical phenomena, including heat transfer, fluid dynamics, structural mechanics, mass transport, diffusion, electromagnetism, and reaction kinetics.
  • Experience applying simulation to real-world systems in industrial settings such as semiconductors, chemical processing, aerospace, or materials manufacturing.
  • Solid programming skills in Python and building simulation workflows, automation pipelines, or custom numerical models.

Bonus Points For
  • Experience bridging atomistic simulations with one or more additional simulation domains including coarse-grained, finite-element and continuum models.
  • Familiarity with machine learning approaches applied to physical simulations (e.g., surrogate models, neural operators, physics-informed neural networks), along with experience leveraging GPU acceleration and programmatic optimization for scalable simulations
  • Experience integrating simulation frameworks into digital twin systems, real-time decision environments, or closed-loop control workflows.
  • Background applying simulation to complex materials and process domains such as thin-film deposition, micro/nano-fabrication, or reactive transport, with an understanding of processing-structure-property relationships.

Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$176,000-$304,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We're All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

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