---
title: 'Machine Learning Engineer at PhysicsX'
canonical: 'https://feeny.ai/job/machine-learning-engineer-physicsx-new-york-2cb69na3d4bk'
type: 'job'
last_seen: '2026-10-15'
---

# Machine Learning Engineer at PhysicsX

- **Company:** PhysicsX
- **Location:** New York, NY
- **Posted:** 2026-04-23
- **Last confirmed live:** 2026-10-15
- **Apply:** https://job-boards.eu.greenhouse.io/physicsx/jobs/4849382101

## Job description

## About us

Re-architecting Engineering for the Age of Intelligence

PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.

Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.

Who We're Looking For

As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.

You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.

With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

Note: This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR).  Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.

This Role

As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.

## What you will do

- Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
- Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
- Explore and manipulate 3D point cloud & mesh data
- Own the delivery of technical workstreams
- Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
- Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
- Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
- Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption

You'll also have the opportunity to travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.

## What you bring to the table

- Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings.
- Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged.
- A track record of scoping and delivering projects in a customer facing role
- 2+ years’ experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
- Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
- Distributed computing frameworks (e.g., Spark, Dask)
- Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
- Containerization and orchestration (Docker, Kubernetes)
- Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
- Excellent collaboration and communication skills - with teams and customers alike
- A background in Physics, Engineering, or equivalent

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)https://www.physicsx.ai/newsroom/how-delivery-makes-physical-ai-work-in-the-real-world

## What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

💰 5% contribution to 401(k) - build long-term security with a strong retirement plan.

🍽️ Free team lunch 1x/week - good food, great company, and space to connect.

🏥 Private health insurance – comprehensive cover for you, offering total peace of mind.

👶 Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

☀️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

📈 Personal development – dedicated support for learning, development, and leveling up over time.

💪 Gympass / Wellhub (subsidized) – for you and up to 3 family members, supporting both physical and mental wellbeing.

💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.

🔎 Watch this space, we’re continuing to build this as we grow…

Salary range:

$150,000 - $190,000 depending on experience Seniority will be assessed throughout our interview process

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.

We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

## About PhysicsX

## Company Overview
- **One-liner**: PhysicsX builds an AI-native software stack for physics simulation and engineering design, enabling advanced industries to accelerate innovation by orders of magnitude.
- **Entity Type**: Private (Series C)
- **Headquarters**: London, United Kingdom
- **Founded**: 2019
- **Founders**: Jacomo Corbo (CEO & Co-Founder) and a Co-Founder & Chairman

## Core Business
- **Primary industries**: Aerospace & Defense, Automotive, Semiconductors, Materials, Energy & Renewables
- **Target customers**: Large industrial organizations (B2B Enterprise) – engineers and teams designing and operating complex physical systems
- **Mission**: Empower industrial organizations to build beyond human imagination and address the defining challenges of our time, with a focus on climate and human health impact

## Products & Services
- **PhysicsX Platform** (SaaS + embedded engineering): An AI-native software stack that unifies simulation, physics AI, data, and engineering applications. Integrates with existing toolchains (CAD, CAE, PLM) and accelerates simulation by orders of magnitude, enabling engineers to explore larger design spaces and move from concept to validated design in days.

## Market Standing
- **Valuation**: Approximately $2.4B (as of Series C in August 2026)
- **Key Metric**: Total funding ~$487M (including $300M Series C, $135M Series B, $32M Series A, $20M from NVentures). Revenue is generating but not publicly disclosed (LinkedIn estimates ~$1M, but company is early-stage revenue generating).
- **Notable Investors/Partners**: Atomico (led Series B), General Catalyst (led Series A), NVentures (NVIDIA’s venture arm), NVIDIA (strategic partner), Siemens (collaboration on data center power infrastructure)
- **Growth Signals**: 
  - Series C oversubscribed $300M at $2.4B valuation (Aug 2026)
  - Headcount growth of 71% YoY (LinkedIn: 226 employees; PitchBook: 350 employees post-C)
  - Forward-deployed engineers embedded in customer programs
  - Open standards for physics AI powered by NVIDIA (March 2026)

## Competitive Advantages
- **True AI-native platform**: Physics AI is built as a core primitive, not bolted onto legacy tooling. Uses advanced models like Fourier Neural Operators to simulate physics at speeds unattainable with traditional CFD/FEA.
- **Embedded deployment model**: Forward-deployed engineers work alongside customers on live problems, ensuring measurable outcomes and deep domain integration.
- **Focus on hardest problems**: Targets extreme complexity (aerospace, semiconductors, climate tech) where speed of development is critical and margins for error are zero.
- **Strategic partnerships**: Deep collaboration with NVIDIA (compute, open standards) and Siemens (infrastructure AI).

## Strategic Focus
- Continue scaling the platform across multiple industrial verticals, with emphasis on the climate transition (energy, materials efficiency) and human health (medical devices, supply chain).
- Expand the "Large Physics Models" research program and open standards initiatives.
- Grow the global team (currently 350+ across UK and US) with strong emphasis on research, product engineering, and forward deployment.

## Why Work Here
- **Culture**: Grounded visionaries, moving fast with trust and ambition. Values include "we make stuff happen" and "we form a community in which people can grow."
- **Work environment**: Hybrid (2-3 days in office per week); offices in London (Shoreditch) and New York (Downtown Manhattan). Visa sponsorship and relocation support available.
- **Benefits**: Generous pension contributions, health insurance, enhanced parental support, development opportunities.
- **Engineering culture**: Work on the hardest problems in industry – physics, AI, and engineering collide. Small, high-autonomy teams. Interview process includes pairing and in-person final rounds.
- **Diversity**: Committed to equal opportunities; strongly encourages underrepresented groups to apply.

## Sources
1. [PhysicsX.ai](https://www.physicsx.ai/) – company website
2. [PhysicsX About](https://www.physicsx.ai/about) – mission, team, challenge
3. [PhysicsX Careers](https://www.physicsx.ai/careers) – culture, benefits, interview process
4. [LinkedIn](https://uk.linkedin.com/company/physicsx) – employee count, funding, headcount growth
5. [PitchBook](https://pitchbook.com/profiles/company/529644-70) – valuation, Series C, founding year

## Other roles at PhysicsX

- [Delivery Engineer](https://feeny.ai/job/delivery-engineer-physicsx-singapore-5wsdrs5mzky7) — Singapore
- [CFD Engineer - Multiphase](https://feeny.ai/job/cfd-engineer-multiphase-physicsx-perth-h3xvsadgm91j) — Perth, Australia
- [Simulation Engineer: FEA & Multi body simulation](https://feeny.ai/job/simulation-engineer-fea-multi-body-simulation-physicsx-new-york-4w9jhnwnw2zm) — New York, NY
- [Staff Software Engineer, Infrastructure - Python & Kubernetes](https://feeny.ai/job/staff-software-engineer-infrastructure-python-kubernetes-physicsx-london-h1qnwfgah3gg) — London, United Kingdom
- [Events & Experiences Manager](https://feeny.ai/job/events-experiences-manager-physicsx-london-hr3ewjq0yfww) — London, United Kingdom
- [Enterprise IT Engineer](https://feeny.ai/job/enterprise-it-engineer-physicsx-new-york-zm2b5bn4hxpq) — New York, NY
- [Lead IT Engineer](https://feeny.ai/job/lead-it-engineer-physicsx-london-q1fk60zjd3m8) — London, United Kingdom
- [Join Our Talent Community](https://feeny.ai/job/join-our-talent-community-physicsx-london-ff82t2dkq2w4) — London, United Kingdom
- [CFD Engineer](https://feeny.ai/job/cfd-engineer-physicsx-new-york-ed2z3r3afh4y) — New York, NY
- [Resourcing Manager (Delivery)](https://feeny.ai/job/resourcing-manager-delivery-physicsx-london-6nb5k6xmx8fw) — London, United Kingdom