PhysicsX is a deeptech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
We are currently recruiting for multiple positions, however, please only apply for the role that best aligns with your skillset and career goals.
PhysicsX is a deeptech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
We are currently recruiting for multiple positions, however, please only apply for the role that best aligns with your skillset and career goals.
Data and AnalyticsDeepTechFinanceInformation TechnologyProfessional ServicesSecuritySoftware
$122M
Company Overview
Problem Domain
Engineering simulation and automation for advanced industries (multiphysics simulation, design optimization, manufacturing and operations).
Founded
2020
Industry
Software Development
Funding Track Record
Series A- November 27, 2023
$32M
Series B- June 22, 2025
$135M
Investor Signal
“Includes strategic participation from Temasek, Siemens, Applied Materials; early lead investor General Catalyst”
Founders
What we do
Join the Team
ML Software Engineer
RemoteUS
Remote • US
About The Company
PhysicsX is a pioneering deep-tech company rooted in numerical physics and with close ties to the high-performance world of Formula One. Our mission is to accelerate hardware innovation by developing advanced AI-driven simulation software for engineering and manufacturing across a broad spectrum of industries. By integrating high-fidelity, multi-physics simulation capabilities through AI inference throughout the entire engineering lifecycle, PhysicsX enables unprecedented levels of optimization and automation in design, manufacturing, and operational processes. Our innovative solutions empower engineers and industry leaders in sectors such as Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive to push the boundaries of technological possibility and achieve breakthroughs that were previously unattainable.
About The Role
We are seeking a talented and motivated Machine Learning Software Engineer with a research focus to join our dynamic team. In this role, you will collaborate closely with research scientists and simulation engineers to develop, optimize, and deploy machine learning models that solve complex real-world physics and engineering problems. Your work will involve designing scalable and efficient models, transforming prototypes into production-ready solutions, and implementing distributed training architectures across multi-node and multi-GPU environments. You will play a key role in building foundation models tailored for scientific and engineering applications, leveraging cloud platforms such as AWS, Azure, and GCP, as well as on-premise infrastructure. This position offers an exciting opportunity to contribute to cutting-edge research, develop reusable libraries and tools, and influence the future of simulation-driven engineering solutions. Mentoring less experienced colleagues and fostering a collaborative environment will also be an integral part of your responsibilities.
Qualifications
Master’s or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or related fields.
Minimum of 1 year of experience in a data-driven or research environment.
Proficiency in scientific computing, high-performance computing (CPU/GPU clusters), and parallel/distributed training for large models.
Responsibilities
Collaborate with research and engineering teams to develop machine learning models addressing complex physics and engineering challenges.
Design, implement, and optimize scalable ML models with a focus on efficiency and performance.
Benefits
Equity options to share in the company's success and growth.
5% 401(k) matching to support your financial future.
Flexible working arrangements to balance work and personal life.
Hybrid work setup with access to our Manhattan office and remote work options.
Enhanced parental leave to support major life milestones.
Comprehensive private healthcare coverage for you and your family.
Opportunities for personal and professional development through training and learning resources.
Work from anywhere to enjoy a flexible and accommodating work environment.
Equal Opportunity
PhysicsX values diversity and is committed to providing equal employment opportunities regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation, or gender identity. We strongly encourage individuals from underrepresented groups in technology to apply.
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Experience with frameworks such as PyTorch, JAX, TensorFlow, and libraries like NumPy, SciPy, Pandas.
Knowledge of cloud computing platforms including AWS, Azure, and GCP.
Hands-on experience with distributed computing frameworks like Spark, Dask, and HPC tools such as MPI, CUDA, Triton.
Strong programming skills in Python, C/C++, and familiarity with software engineering best practices, including version control, testing, CI/CD, and API design.
Experience with containerization and orchestration tools like Docker, Kubernetes, and Slurm.
Understanding of MLOps principles and experience building machine learning pipelines and experiment management systems.
Excellent problem-solving, communication, and collaboration skills.
Transform research prototypes into robust, production-quality implementations suitable for deployment at scale.
Develop distributed training architectures utilizing multi-GPU and multi-node setups, including federated learning approaches.
Work with scientists to design and scale foundation models tailored for scientific applications, optimizing training processes for large datasets and cloud environments.
Identify and evaluate appropriate libraries, frameworks, and tools to support modeling efforts and ensure project success.
Lead or contribute to research work streams, sharing insights and results with internal teams and external stakeholders.
Translate research outcomes into reusable software libraries, tools, and products that enhance our simulation capabilities.
Mentor junior team members, fostering a collaborative and growth-oriented environment.
Engage in technical discussions, present findings, and recommend solutions to address real-world physics and engineering problems.
Competitive salary range of $120,000 to $240,000, commensurate with experience.
