The Role
PhysicsX is a deep-tech 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.
Note: We do not provide visa sponsorship in the US. Please only apply if you have the right to work in the US.
We are currently hiring for several positions. Please apply for one role that best aligns with your skills and career goals, and our hiring team will evaluate where your profile and motivations are the best fit.
Who We're Looking For
As a Data Scientist in Delivery, you are a problem solver and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side-by-side with them on-site) to transform cutting edge AI models into tools that are useful and used.
You’ve worked on difficult problems that require strong foundations in data driven modelling and deep learning techniques, with hands-on experience in probabilistic methods and predictive modelling. Expertise in python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with the ability to deploy scalable, production-ready models and data pipelines.
With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re truly excited about growing your technical expertise and are naturally inclined to take ownership of data science work streams, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
This Role
In this role, you’ll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving.
You’ll build the foundations for successful, impactful solutions by:
- Pre-processing and analyzing data to prepare it for use in predictive modelling, building the foundation for machine learning algorithms to be developed.
- Developing and utilizing innovative deep learning models in combination with state-of-the-art optimization methods to predict and control the behaviour of physical systems.
- Taking full responsibility for the quality, accuracy and impact of your work.
- Designing, building and testing data pipelines that are reliable, scalable and easily deployable in production environments.
- Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
- Contributing to internal R&D and product development, helping to refine models and identify new areas of application.
- Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.
- There is a requirement to travel to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you’ll collaborate closely with customers to build solutions on site.
As the role evolves, there are exciting opportunities for growth as an individual contributor or a technical lead, especially if you’re driven by taking ownership of more complex projects and leading the direction of future solutions.
Please note, this role is based in Manhattan, NYC, working 2-3 days per week in our office.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey! https://www.physicsx.ai/newsroom/how-delivery-makes-physical-ai-work-in-the-real-world
What we offer
- Equity options – share in our success and growth.
- 5% 401(k) match – invest in your future.
- Flexible working – balance your work and life in a way that works for you.
- Hybrid setup – enjoy our Manhattan office while keeping remote flexibility.
- Enhanced parental leave – support for life’s biggest milestones.
- Private healthcare – comprehensive coverage for you and your family.
- Personal development – access learning and training to help you grow.
- Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.
Our stance
We believe diversity fuels innovation, and we're building a culture where everyone belongs. We're proud to be an equal opportunity employer, welcoming talent of all backgrounds, identities, and experiences. Changing the face of tech takes action, which is why we actively encourage individuals from historically underrepresented groups to apply.
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The Company
What We Do
PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to accelerate physics simulations and enable a new frontier of optimization opportunities in design and engineering. Born out of numerical physics, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational product performance. We do this in some of the most advanced and important industries of our time – including Space, Aerospace, Medical Devices, Additive Manufacturing, Electric Vehicles, Motorsport, and Renewables. Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, and increasing the performance of wind turbines. We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals. We do not currently offer work experience
