PhysicsX
PhysicsX is a physical AI company on a mission to accelerate innovation and overhaul what engineering and manufacturing look like today. We are building a new software stack to deliver deep AI enablement across the entire engineering lifecycle. We partner with leading organizations in aerospace & defense, 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 and New York.
Last year we raised $155 million as part of its Series B financing. The round was led by Atomico, with participation from Temasek, Nvidia, Siemens, Applied Materials, and July Fund, as well as continued support from existing investors including General Catalyst, NGP, Radius Capital, Standard Investments, and Allen & Co.
Learn more about how we work: https://www.physicsx.ai/careers.
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About us
The role
What you’ll do
- Partner directly with customers to assess their infrastructure requirements, security constraints, and deployment preferences, serving as the primary technical point of contact throughout the deployment lifecycle
- Build and maintain strong relationships with customer technical teams and stakeholders
- Gather customer feedback and requirements to inform platform development priorities
- Design and execute deployment strategies for customer-owned cloud and on-premise infrastructure
- Troubleshoot complex deployment issues across diverse infrastructure environments, understanding the difference between application and infrastructure bugs and triage internally
- Act as a system validator to ensure our platform works within customer infrastructure
- Continuously apply and improve deployment best practices and standards, and coach colleagues in their adoption
- Travel to customer sites in APAC for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site
What we’re looking for
- Experience in deploying Kubernetes clusters across a range of cloud platforms (AWS, Azure) and on-premise infrastructure
- Experience with infrastructure-as-code tools, preferably Crossplane, Terraform, and Helm
- Understanding of networking, security, and observability in containerised environments
- Proven track record of working directly with external customers or clients
- Excellent communication skills with the ability to explain complex technical concepts to diverse audiences, including managing expectations and delivering on commitments
- Strong problem-solving skills with a customer-first mindset
- Comfortable presenting to technical and business stakeholders
- Self-motivated with strong project management and organisational skills to empower internal and external teams to prioritise effectively
- Collaborative approach with the ability to work effectively across various teams
- Experience in a customer-led, customer success, professional services, or solutions engineering role is a plus
- Experience in regulated industries or high-security environments is a plus
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 Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
Ready to apply?
Apply to PhysicsX
About us
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
The Role
Your role, first and foremost, is to help our customers solve their most important problems. As a Software Engineer, this takes the form of building and deploying applications that utilize the power of our physics AI models to enable our customers to build better, faster, and cheaper.
Who We're Looking For
What a day might look like
Ready to apply?
Apply to PhysicsX
About us
Who We're Looking For
As a Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, 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 and make pragmatic product decisions that set Delivery up for success. 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 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. 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.
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.
You'll:
- Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments.
- Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
- Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
- Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
- Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure.
- 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.
- Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.
As an early member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.
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!
Ready to apply?
Apply to PhysicsX
About us
We're looking for a proactive, organised, and versatile Executive Assistant & Office Manager to support our growing Asia-Pacific team and help build and run our new Singapore office from the ground up. This is a primarily office-based role ideal for someone who enjoys a varied mix of responsibilities, working closely with leadership and contributing to a vibrant, diverse, and social team culture.
Key Responsibilities
Executive Assistant Support
- Provide high-quality, proactive support to senior leadership in the APAC region, including diary management, internal and external meeting coordination, travel arrangements and other tasks as needed.
- Provide support to other team members with scheduling as needed.
- Collaborate with global Executive Assistants to manage scheduling, priorities, and cross-regional alignment.
- Coordinate logistics for internal and external meetings (both in-person and virtual), including workshops, customer events, etc.
- Ensure timely processing of expenses.
- Suppor domestic and international travel for the APAC team using the company's travel booking system.
- Cover for other Executive Assistants globally.
Office Management
- Play a key role in setting up and establishing our new Singapore office, including coordinating logistics, sourcing suppliers, and creating efficient ways of working from day one.
- Support the smooth operation of the Singapore office on an ongoing basis, including managing supplies, vendors, and facilities.
- Act as the first point of contact for all guests and office-related queries, ensuring a positive and efficient work environment.
- Ensure office compliance, including health and safety regulations, local workplace requirements, and company policies.
- Assist with the planning, coordination and execution of team events, meetings, and social activities.
- Liaise with the global Operations team to ensure alignment on tools, processes, and standards across offices.
Key Skills Required
- Demonstrated experience in Office Management and Executive Assistant roles, ideally within a fast-paced or high-growth environment.
- Ability to anticipate needs, prioritise effectively, and understand the broader context when making decisions or supporting the leadership team.
- Exceptional attention to detail, ability to manage multiple tasks and stay calm under pressure.
- Clear, professional communicator across written, verbal, and digital channels.
- Able to handle sensitive information with a high degree of confidentiality and discretion.
- Comfortable with shifting priorities and flexible to support a growing, fast-paced organisation.
- Enjoys working with diverse personalities, building relationships, and contributing to a social, inclusive team environment.
- Proactive attitude.
- Ideally experience working across time zones and for an international company.
- Confident using Microsoft Office (Outlook, Word, Excel, PowerPoint) and travel booking systems.
Ready to apply?
Apply to PhysicsX
About us
Who We’re Looking For
As a Senior CFD Engineer (Delivery), you are a problem solver and a builder, who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly with customers (often directly on-site) to build CAE models that are integrated into AI-tools that are both useful and used.
You bring deep expertise in fluid mechanics, heat transfer, and multiphase modelling, with a solid ability to apply fundamental knowledge to real-world phenomena across a wide range of engineering applications. Highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent and adept at automating these tools to create scalable optimisation workflows that drive impactful results. Experience in parametric CAD modelling (NX or CATIA) and coding in Python/Java, (or the ability to quickly learn programming languages), is an advantage.
With 3-5 years of industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re confident setting up CFD simulations independently, interpreting complex results with depth, and making informed decisions based on solid engineering judgement.
This Role
In this role, you’ll work closely with our Data Scientists, Machine Learning Engineers, and customers to understand and define the engineering challenges we are solving.
You’ll play a crucial role in delivering high-fidelity simulations by:
- Independently building complex multi-physics models from geometry clean-up and meshing, to simulating and post-processing complex real-world phenomena, integrating experimental data for model validation.
- Building robust parametric CAD models (NX or CATIA) coupled with simulation pipeline automation, for executing advanced design optimization and DoE studies.
- Partner with customers to address their most complex engineering challenges through advanced CAE & AI solutions; present results clearly, recommend actionable next steps, and balance accuracy with efficiency under tight deadlines.
- Working at the intersection of CAE and Data Science to generate high-quality simulation datasets for training Machine/Deep Learning models. Leveraging data sampling techniques to efficiently capture the design space, reduce computational cost, and enhance model accuracy.
- Accelerate high-fidelity modelling by using Flux (our cloud platform) and on-premise HPC resources, going beyond smart meshing and model setup to achieve real performance gains.
- Continuously improving engineering best practices, adapting CFD model setups and outputs to support the development of Deep Learning surrogates.
- Combining project leadership with a strong commitment to mentoring junior colleagues, contributing to a culture of collaboration, growth, and shared success.
- Traveling globally (North America, Europe, Asia, Oceania) up to 2–3 weeks per quarter to work side-by-side with customers in building solutions on-site.
As the role evolves, there are exciting opportunities for growth as an Individual Contributor (IC) or a Team Lead (TL), especially if you’re driven to take ownership of more complex projects and lead the direction of future solutions.
Ready to apply?
Apply to PhysicsX
About us
The Role
Your role, first and foremost, is to help our customers solve their most important problems. As a Senior Forward Deployed Software Engineer, this takes the form of building and deploying applications that utilize the power of our physics AI models to enable our customers to build better, faster, and cheaper.
Who We're Looking For
What a day might look like
Ready to apply?
Apply to PhysicsX
About us
Who We’re Looking For
As a Senior FEA Engineer (Delivery), you are a problem solver and a builder, who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly with customers (often directly on-site) to build CAE models that are integrated into AI-tools that are both useful and used.
You bring deep expertise in structural mechanics, materials science, and multi-physics modelling, with a solid ability to apply fundamental knowledge to real-world phenomena across a wide range of engineering applications. Highly proficient in at least one of NASTRAN, ABAQUS or ANSYS Mechanical, adept at automating these tools to create scalable optimisation workflows that drive impactful results. Experience with open source FEA packages such as CalculiX or FEniCS would be highly advantageous. Proficiency in parametric CAD modelling (NX or CATIA) and coding in Python, (or the ability to quickly learn programming languages), is an advantage. Experience with explicit dynamics (LS-DYNA, Abaqus/Explicit) such as crash simulation is highly valued. Background in coupled simulations such as thermo-mechanical analysis and fluid-structure interaction modelling also is highly desirable.
With 3-5 years of industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re confident setting up FEA simulations independently, interpreting complex results with depth, and making informed decisions based on solid engineering judgement.
This Role
In this role, you’ll work closely with our Data Scientists, Machine Learning Engineers, and customers to understand and define the engineering challenges we are solving.
You’ll play a crucial role in delivering high-fidelity simulations by:
- Independently building complex structural and multi-physics models from geometry clean-up and meshing, to simulating and post-processing complex real-world phenomena, integrating experimental data for model validation.
- Building robust parametric CAD models (NX or CATIA) coupled with simulation pipeline automation through scripting, for executing advanced design optimization and DoE studies.
- Partner with customers to address their most complex engineering challenges through advanced FEA & AI solutions; communicate results clearly, recommend actionable next steps, and balance accuracy with efficiency under tight deadlines.
- Working at the intersection of CAE and Data Science to generate high-quality simulation datasets for training Machine/Deep Learning models. Leveraging data sampling techniques to efficiently capture the design space, reduce computational cost, and enhance model accuracy.
- Accelerate high-fidelity modelling by using Flux (our cloud platform) and on-premise HPC resources, going beyond smart meshing and model setup to achieve real performance gains.
- Continuously improving engineering best practices, adapting FEA model setups and outputs to support the development of Deep Learning surrogates.
- Documenting workflows and results comprehensively via technical reports and process documentation that enable knowledge transfer and support reproducible engineering methodologies
- Combining project leadership with a strong commitment to mentoring junior colleagues, contributing to a culture of collaboration, growth, and shared success.
- Traveling globally (North America, Europe, Asia, Oceania) up to 2–3 weeks per quarter to work side-by-side with customers in building solutions on-site.
As the role evolves, there are exciting opportunities for growth as an Individual Contributor (IC) or a Team Lead (TL), especially if you’re driven to take ownership of more complex projects and lead the direction of future solutions.
Ready to apply?
Apply to PhysicsX
About us
Who We're Looking For
As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, 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 and make pragmatic product decisions that set Delivery up for success. 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 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. 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.
This Role
As a Principal MLE, 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.
You'll:
- Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments.
- Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
- Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
- Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
- Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure.
- 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.
- Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.
As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.
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!
Ready to apply?
Apply to PhysicsX