At a Glance
- Tasks: Design and build high-performance systems for AI workloads across distributed clusters.
- Company: Join Flux, a pioneering company developing cutting-edge AI accelerators in London.
- Benefits: Enjoy a competitive salary, stock options, and a £24k/year incentive for nearby living.
- Why this job: Be at the forefront of AI innovation, shaping performance layers and collaborating with top talent.
- Qualifications: 5+ years in HPC or AI infrastructure, strong C++ and Python skills, and experience with ML compilers.
- Other info: Work in a vibrant office in Kings Cross, London, within a dynamic and innovative team.
The predicted salary is between 104000 - 186000 £ per year.
Company Overview
Flux is pioneering a new class of AI accelerators called Optical Tensor Processing Units (OTPUs). We’ve already developed functioning prototypes and are now scaling our operations in London. Our work environment rewards innovation, speed, and bold thinking.
The role
We’re hiring Senior and Staff Software Engineers to build the high-performance computing infrastructure that powers our Optical Tensor Processing Units (OTPUs). This isn’t just about scaling models—it’s about rethinking how AI workloads are executed at speed and scale.
You’ll lead the design and implementation of software systems that run distributed, low-latency inference across clusters. You’ll work closely with hardware and ML teams to optimise every layer of the stack—from model representation and execution to data movement and scheduling. Whether it’s through compiler techniques, systems-level tuning, or custom runtime design, you’ll play a critical role in shaping the performance layer of our AI platform. This is a role for engineers who think in microseconds, not just model accuracy. If you’ve worked in HFT, large-scale scientific compute, or AI infrastructure at serious scale, we’d love to talk.
Responsibilities
- Design and build high-performance systems for running AI/ML workloads across distributed compute clusters
- Optimise for ultra-low latency and real-time inference at scale—profiling, tuning, and rewriting critical systems as needed
- Identify and resolve performance bottlenecks across the stack, from model execution and scheduling to hardware-level constraints
- Collaborate with compiler engineers to improve code generation, execution paths, and memory layouts using tools like LLVM or MLIR
- Work with hardware teams to ensure the software stack fully leverages the capabilities of our OTPU architecture
- Extend ML frameworks (e.g. PyTorch, ONNX, OpenXLA) to better support performance-critical inference paths
- Lead design reviews, mentor engineers, and promote best practices in HPC and performance engineering
- Stay on the frontier of new developments in AI infrastructure, compute systems, and compiler tooling
Skills & Experience
- 5+ years of experience building performance-critical systems in HPC, HFT, large-scale simulation, or AI infrastructure
- Deep understanding of distributed systems, with a focus on real-time or near real-time data processing
- Strong programming skills in C++ and Python, especially for performance-sensitive applications
- Hands-on experience with ML compilers (e.g. LLVM, MLIR), and knowledge of runtime and scheduling optimisations
- Practical knowledge of ML frameworks like PyTorch, ONNX, or OpenXLA, and how to optimise their execution
- Experience scaling AI workloads across clusters or custom infrastructure—not just deploying on standard cloud setups
- Strong debugging, profiling, and performance-tuning skills across the stack
- Degree in Computer Science, Engineering, Mathematics, or a related field
Details
- Competitive salary ranging from £145k+, depending on experience.
- Stock options in a rapidly growing AI company.
- Based in our new 5,000 sq. ft. office in the AI hub of Kings Cross, London.
- Flux hires candidates within a 45-minute commute of our office—offering an extra £24k/year incentive if you choose to live within 20 minutes.
Senior / Staff Software Engineer employer: Flux Computing
Contact Detail:
Flux Computing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior / Staff Software Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in AI infrastructure and Optical Tensor Processing Units (OTPUs). Understanding the technology behind OTPUs will not only help you during interviews but also demonstrate your genuine interest in Flux's innovative work.
✨Tip Number 2
Network with professionals in the HPC and AI fields, especially those who have experience with performance-critical systems. Engaging with industry experts can provide valuable insights and potentially lead to referrals that could boost your application.
✨Tip Number 3
Prepare to discuss specific projects where you've optimised performance in distributed systems. Be ready to share your thought process on identifying bottlenecks and the techniques you used to overcome them, as this aligns closely with the responsibilities of the role.
✨Tip Number 4
Stay updated on tools like LLVM and MLIR, as well as frameworks such as PyTorch and ONNX. Being able to speak knowledgeably about these technologies and how they relate to performance tuning will set you apart from other candidates.
We think you need these skills to ace Senior / Staff Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in building performance-critical systems, especially in HPC, HFT, or AI infrastructure. Use specific examples that demonstrate your skills in C++ and Python, as well as your understanding of distributed systems.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and high-performance computing. Mention how your background aligns with the responsibilities outlined in the job description, particularly your experience with ML compilers and optimising AI workloads.
Showcase Relevant Projects: If you have worked on projects related to AI infrastructure or performance tuning, be sure to include them in your application. Describe your role, the technologies used, and the impact of your contributions on the project's success.
Highlight Collaboration Skills: Since the role involves working closely with hardware and ML teams, emphasise your ability to collaborate effectively. Provide examples of past experiences where you successfully worked in cross-functional teams to achieve project goals.
How to prepare for a job interview at Flux Computing
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with performance-critical systems, especially in HPC or AI infrastructure. Highlight specific projects where you've optimised for low latency and real-time inference, as this aligns closely with the role's requirements.
✨Demonstrate Problem-Solving Skills
Expect technical questions that assess your ability to identify and resolve performance bottlenecks. Prepare examples of how you've tackled similar challenges in the past, focusing on your thought process and the impact of your solutions.
✨Familiarise Yourself with Relevant Tools
Brush up on your knowledge of ML compilers like LLVM and MLIR, as well as frameworks such as PyTorch and ONNX. Be ready to discuss how you've used these tools to optimise execution paths and memory layouts in previous roles.
✨Emphasise Collaboration and Leadership
Since the role involves working closely with hardware and ML teams, be prepared to talk about your experience in collaborative environments. Share instances where you've led design reviews or mentored other engineers, showcasing your leadership skills.