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Machine Learning • Software
As a Software Engineer, you will develop and maintain machine learning libraries focusing on performance and scalability, while owning the software lifecycle and collaborating with cross-functional teams.
Top Skills:
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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.
The Role
PhysicsX is developing a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. The core of this platform is powered by several Machine Learning Python Libraries handling everything from data processing, to deep learning model training, and complex optimisation algorithms.
The Libraries team is responsible for designing, developing, and maintaining those Machine Learning Libraries. As a Software Engineer within the team, you will focus on the underlying engineering that makes our libraries fast, scalable, and a pleasure to use. You are a software craftsperson who champions best practices, ensuring that our entire development lifecycle—from code design to CI/CD—is robust and maintainable. Your work provides the solid foundation upon which our machine learning innovations are built.
What you will do
- Collaborate with product managers, machine learning engineers, and library users to translate functional requirements into robust technical specifications and production-ready code code.
- Architect, build, and maintain the foundational software of our internal Machine Learning libraries, with a relentless focus on performance, and scalability.
- Contribute high-quality, tested, documented, and maintainable code across the library stack, ensuring our core systems are reliable and easy for other engineers to build upon.
- Champion software engineering excellence across the team and company, driving best practices in testing (unit, integration, performance), CI/CD, and system architecture.
- Own your work end-to-end, from ideation and experimentation through to deployment and maintenance in a small, agile team environment.
- Continuously explore and evaluate new techniques and frameworks, helping to guide the technical evolution of our platform.
- Share your knowledge with the team, contribute to our engineering guild, and stay connected with the broader community.
What you bring to the table
- A passion for the craft of software engineering and building robust, maintainable systems in a collaborative, cross-functional team.
- Solid software engineering skills, with a focus on writing clean, testable, and maintainable code.
- A commitment to owning the software development lifecycle, including testing, containerization, and CI/CD.
- Expert-level proficiency in modern Python, with a deep understanding of its performance characteristics, design patterns, and packaging.
- Familiarity with building performant and reliable Python systems, including low-level C/C++ extensions (e.g., using pybind11, Cython) and instrumentation for production telemetry (e.g., Prometheus, OpenTelemetry).
- A proactive ownership mindset and the ability to navigate ambiguity.
- Excellent collaboration and communication skills for working effectively with teams and stakeholders.
Ideally
- Professional experience GPGPU programming (e.g., CUDA, Triton) for performance optimization.
- Experience building and maintaining widely-used internal or open-source libraries.
- Familiarity with the machine learning development lifecycle and core concepts (e.g., bias-variance tradeoff, common optimizers).
- Familiarity with 3D geometric data structures and algorithms.
What we offer
- Equity options – share in our success and growth.
- 10% employer pension contribution – invest in your future.
- Free office lunches – great food to fuel your workdays.
- Flexible working – balance your work and life in a way that works for you.
- Hybrid setup – enjoy our new Shoreditch office while keeping remote flexibility.
- Enhanced parental leave – support for life’s biggest milestones.
- Private healthcare – comprehensive coverage
- 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.
PhysicsX New York, New York, USA Office
2nd Floor 154 W 14th Street, New York, NY, United States, 10011
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
