At a Glance
- Tasks: Design and build high-performance systems for AI workloads across distributed clusters.
- Company: Flux is revolutionising AI with cutting-edge Optical Tensor Processing Units in London.
- Benefits: Competitive salary, stock options, and a £24k/year incentive for nearby living.
- Why this job: Join a fast-paced environment that values innovation and bold thinking in AI technology.
- Qualifications: 5+ years in HPC or AI infrastructure, strong C++ and Python skills, and ML compiler experience.
- Other info: Work in a vibrant office in Kings Cross, London, at the heart of the AI hub.
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 (AI / Compiler) employer: Flux Computing
Contact Detail:
Flux Computing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior / Staff Software Engineer (AI / Compiler)
✨Tip Number 1
Familiarise yourself with the latest advancements in AI infrastructure and compiler technologies. Being well-versed in tools like LLVM or MLIR will not only help you understand the role better but also demonstrate your commitment to staying at the forefront of the field.
✨Tip Number 2
Network with professionals in the HPC and AI sectors. Attend relevant meetups, webinars, or conferences to connect with potential colleagues or mentors who can provide insights into the company culture and expectations at Flux.
✨Tip Number 3
Prepare to discuss specific projects where you've optimised performance-critical systems. Be ready to share your thought process on identifying bottlenecks and how you approached solving them, as this will showcase your hands-on experience.
✨Tip Number 4
Research Flux's current projects and their Optical Tensor Processing Units (OTPUs). Understanding their technology and how it differs from traditional AI accelerators will allow you to tailor your discussions and show genuine interest in their work.
We think you need these skills to ace Senior / Staff Software Engineer (AI / Compiler)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in high-performance computing, AI infrastructure, and distributed systems. Emphasise your programming skills in C++ and Python, as well as any hands-on experience with ML compilers like LLVM or MLIR.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and performance engineering. Discuss specific projects where you've optimised systems for low-latency inference and how your background aligns with the responsibilities outlined in the job description.
Showcase Relevant Projects: Include a section in your application that showcases relevant projects or achievements. Highlight any experience you have with scaling AI workloads, debugging, profiling, and performance tuning across the stack.
Prepare for Technical Questions: Anticipate technical questions related to distributed systems, compiler techniques, and performance optimisation. Be ready to discuss your problem-solving approach and provide examples from your past work that demonstrate your expertise.
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 Collaboration Skills
Since the role involves working closely with hardware and ML teams, be ready to share examples of how you've successfully collaborated in cross-functional teams. Discuss any experiences where you’ve led design reviews or mentored other engineers.
✨Familiarise Yourself with Relevant Tools
Brush up on your knowledge of ML compilers like LLVM or MLIR, and be ready to discuss how you've used these tools to improve code generation and execution paths. Showing familiarity with performance tuning and debugging techniques will also be beneficial.
✨Stay Updated on Industry Trends
Research the latest developments in AI infrastructure and compiler tooling. Being able to discuss current trends and how they might impact the role will demonstrate your passion for the field and your commitment to staying at the forefront of technology.