Software Engineer - Simulation 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 Data Engineering 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 visualize and understand their results. 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

• Design and build scalable distributed systems, microservices, and APIs focused on storing, processing, and serving high-dimensional simulation data.

• Create robust, automated data and analytical pipelines that ingest, process, and transform multimodal data from physics simulations to feed our AI training loops and inference engines.

• Implement and integrate with modern Data Warehouses and Data Lakes (or Data Lakehouses) to ensure our data is organized, accessible, and queryable at scale.

• Build internal BI systems and complex scientific data visualizations that allow researchers and engineers to interact intuitively with massive datasets and simulation results.

• Implement high-performance storage solutions capable of handling the unique demands of complex simulations and deep learning workloads.

• Drive best practices in software engineering across the team, including CI/CD, automated testing, and infrastructure-as-code, ensuring our data systems are as reliable as they are powerful.

• Own your work from architectural design and prototyping through to deployment and maintenance in a fast-paced, agile environment.

What you bring to the table

• A passion for the evolving craft of software engineering and for sponsoring a culture of excellence in the craft.

• A strong foundation in software engineering (algorithms, data structures, system design) with a passion for writing clean, maintainable, and testable code (strong command of Golang and Python).

• Proven experience building distributed systems with big data processing pipelines in a production environment, moving beyond simple scripting to robust engineering solutions (e.g. Databricks/Delta Lake, Snowflake, BigQuery), practical experience integrating with and architecting around Data Warehouses and Data Lakes.

• Experience building custom data visualizations or integrating complex BI systems to expose data insights to end-users.

• A proactive mindset with the ability to diagnose complex performance bottlenecks in data processing and storage systems.

• Excellent communication skills to discuss data needs with research scientists and translate them into technical specifications.

Ideally

• Polyglot Programming Mastery: deep expertise in Python combined with mastery of high-performance compiled languages such as Golang, C++, or Rust.

• Big Data Scale: Real-world experience designing and maintaining big data systems, with a proven track record of running complex analytics on massive datasets in production.

• Multimodal Data Exposure: Experience working with multimodal databases or storage engines capable of handling diverse data types (e.g., combining relational data, vector embeddings, and large binary blobs) seamlessly.

• Domain Knowledge: Understanding of 3D geometry processing (meshes, point clouds) and the specific data structures used in physics-based simulations.

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 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 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.