PhysicsX
Senior Machine Learning Software Engineer, Research
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Senior Machine Learning Software Engineer, Research
PhysicsX: Deep Tech Simulation Engineering Leadership
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
- Automotive
Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.
What You Will Do
- Shape Research group strategy and culture in key domains
- Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, particularly:
- Scaled engineering
- Securing compute
- Infrastructure stack
- Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, particularly:
- Define necessary profiles to execute this strategy
- Promote effective working patterns, and proactively flag team dynamic issues for a productive environment
- Nurture younger colleagues by guiding their skillset and professional development
- Own Research work-streams at a high-level to deliver outcomes
- Align priorities with internal and external stakeholders to meet goals
- Set the technical direction and apply judgement to drive progress
- Plan structured roadmaps with clear milestones for strategic decisions
- Organise and guide junior members to execute and deliver roadmap targets
- Communicate purpose and outcomes to raise company-wide awareness and enable adoption
Core Activities:
- Collaborate with researchers and simulation engineers to build models addressing real-world physics problems
- Design, build, and optimise machine learning models focused on scalability and efficiency within our domain
- Transform prototypes into robust, production-ready implementations
- Implement distributed training architectures (e.g., data parallelism, parameter server) and investigate federated learning using:
- Cloud frameworks (AWS, Azure, GCP)
- On-premise services
- Work with scientists to design, build, and scale foundation models in science/engineering
- Ensure optimised training for large datasets and multi-GPU cloud infrastructure
- Select optimal libraries, frameworks, and tools to support modelling efforts
- Discuss the implications of research outcomes to address real-world problems
- Translate Research into reusable libraries, tools, and products, bridging data science and software engineering
- Foster a supportive environment for colleagues with less experience in ML/Engineering to grow
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What You Bring To The Table
We seek candidates with:
- Enthusiasm for developing machine learning solutions, especially deep learning and probabilistic methods, in science and engineering applications
- Ability to work autonomously, scope, and deliver projects across diverse domains
- Strong problem-solving skills with analytical rigour
- Excellent collaboration and communication skills (internal teams and customers)
- Relevant academic background:
- MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or related fields
- Record of experience in:
- Scientific computing
- High-performance computing (CPU/GPU clusters)
- Parallelised/distributed training for large/foundation models
Required professional experience (4+ years):
- Scaled and optimised ML models, trained foundation models (federated learning bonus)
- Employed frameworks/tools:
- Distributed computing (Spark, Dask)
- High-performance frameworks (MPI, OpenMP, CUDA, Triton)
- Cloud computing on hyper-scalers (AWS, Azure, GCP)
- Developed models/pipelines using:
- Python libraries/frameworks (NumPy, SciPy, Pandas, PyTorch, JAX), especially deep learning
- C/C++ for tasks like computer vision, geometry, or scientific computing
- Demonstrated software engineering best practices:
- Versioning, testing, CI/CD, API design, MLOps
- Containerised/orchestrated compute via Docker, Kubernetes, Slurm
- Authored pipelines, experiment environments, and systematic methods for reproducible training/experiments
What We Offer
Impact-Driven Work
Build technology that matters across industries. Work on problems that deliver real-world impact—redefining engineering boundaries with an AI-native approach.
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Collaborative Culture
Join a team of exceptional engineers, scientists, and operators driven by excellence and camaraderie. Diversely skilled yet unified by a commitment to addressing formidable challenges. Ambitious, thoughtful, and vision-driven individuals will thrive.
Influence Over Hierarchy
Adopt a flat operating structure; great ideas win regardless of source. Question assumptions and challenge norms—they inspire innovation and continuous progress.
Sustainable Focus & Growth
Combine long-term ambition with work-life balance. A hybrid model offers:
- Shoreditch office/remote flexibility
- Flexibility
- Meaningful permanence with growth-focused structures
Perks & Benefits
- Equity options: Share meaningfully in the company’s building journey
- 10% employer pension contribution for long-term financial planning
- Free office lunches to sustain energy and focus
- Enhanced parental leave: 3-months full pay (paternity), 6-months (maternity)
- YellowNest nursery scheme to support working parents with childcare costs
- 25 days Annual Leave (+ public holidays) to emphasize wellness
- Private medical insurance: Full coverage for peace of mind
- Wellhub Subscription: Access to global gyms, wellness apps, and fitness classes
- Inflation-adjusted eye tests for ergonomic health
- Personal development support: Investing in continuous growth at every career stage
- Employee Assistance Programme: Confidential wellbeing resources available anytime
- Bike2Work/Season ticket loan for sustainable commuting options
- Octopus EV salary sacrifice scheme for seamless electric vehicle adoption
Commitment to Diversity & Inclusion
PhysicsX embraces equal opportunity irrespective of sex, race, religion, disability, age, sexual orientation, or gender identity. We actively sponsor underrepresented groups, including bright women from disadvantaged backgrounds in STEM fields, to foster diverse talent.
We maintain anonymised diversity data collection only for policy monitoring, ensuring UK compliance and aggregation without influencing applications.
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