Software Engineer - AI Workbench

About us

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 relies on handling massive volumes of complex simulation data, enabling high-fidelity multi-physics simulation through AI inference.

We are looking for a Software Engineer with a strong background in building data platforms to join our team. You will not just be moving data from A to B; you will be architecting and building the distributed systems, services, and APIs that form the backbone of our data strategy. You will bridge the gap between complex physical simulations and modern data infrastructure, implementing storage solutions for AI/ML pipelines and creating the analytical layers that allow our engineers to visualise and understand their results.

You will also play a key role in shaping technical direction — contributing to Technical Decision Records, collaborating with experienced engineers, and helping to drive the standards that keep our platform reliable, secure, and performant. This is a role for a builder who loves coding robust software as much as they love designing efficient data architectures.

What you will do

• Contribute to the design and build scalable microservices, APIs, and data pipelines for high-dimensional simulation data across the ML lifecycle, working within established architectural patterns.
• Build and maintain automated data ingestion and processing pipelines that power active learning loops, serving both no-code and pro-code users.
• Implement and integrate data infrastructure components (Data Warehouses, Data Lakes, storage solutions) for simulation and deep learning workloads.
• Build internal tools that enable BI dashboards and scientific data visualizations, making large datasets intuitive and accessible.
• Own features end-to-end — from implementation through testing, deployment, and maintenance — writing clean, well-tested, secure code.
• Contribute to reliability standards, performance monitoring, and quality of service metrics. Identify and help resolve performance bottlenecks.
• Follow and contribute to API schema standards, security practices, and data access control patterns.
• Participate in CI/CD pipeline maintenance, automated testing, and observability practices, including supporting zero-downtime deployments.
• Participate in code reviews, knowledge sharing, and cross-functional collaboration with data scientists and researchers.
• Contribute to Technical Decision Records and team discussions on tooling and architectural trade-offs.

What you bring to the table

• A passion for the craft — you're driven by engineering excellence and committed to fostering that culture across the team.
• Strong software engineering foundations — solid grasp of algorithms, data structures, and system design. You write clean, maintainable, testable code in Python with working knowledge of Golang or Rust.
• Data platform exposure — experience building or contributing to data processing systems in production. Familiarity with tools like Databricks, Snowflake, or BigQuery and concepts around Data Warehouses and Data Lakes.
• API and service design — experience working with multi-service architectures, understanding schema design and data access patterns.
• Security and reliability awareness — understanding of security fundamentals, monitoring, alerting, and quality of service in production systems.
• CI/CD familiarity — practical experience with CI/CD pipelines and deployment workflows.
• Safe code execution awareness — understanding of or interest in sandboxing, isolation, and security considerations for running user-submitted code.
• Problem-solving — ability to diagnose issues, debug across services, and optimize data processing performance.
• Communication and collaboration — strong communication skills for working with cross-functional teams. Comfortable participating in code reviews and supporting peers.
• Incremental mindset — you work in small steps, balance detail with the big picture, and proactively seek help when blocked.

Ideally

• Programming skills: strong Python expertise and experience with at least one compiled language (Golang, C++, or Rust).
• Data systems experience: practical experience building and maintaining data processing systems, working with diverse data types and running analytics on large datasets.
• Kubernetes and infrastructure: familiarity with Kubernetes concepts and infrastructure configuration tools (e.g., Helm, ArgoCD).
• Testing and debugging: solid debugging and troubleshooting skills, with exposure to automated testing practices.
• Bonus: understanding of 3D geometry processing, physics simulation data structures, or building software for different deployment environments (cloud, on-premises).

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.

And it doesn’t stop there …

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

🏦10% employer pension contribution - because investing in future matters.

🍽️Free office lunches - to keep you energised and focused.

👶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.

🍼YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀Eye tests - because good work depends on good health.

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

💛Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲Bike2Work scheme and 🚆Season ticket loan - to make getting to work easier and greener.

🚗Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

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

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 UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.