Senior / Staff Software Engineer (AI / Compiler)

JR United Kingdom; Luton; On-site; GBP 145,000 - 180,000; Full time

Job summary

A pioneering AI company seeks a Senior/Staff Software Engineer to enhance its high-performance computing infrastructure. This role involves leading the design of systems for distributed AI workloads, requiring a deep understanding of HPC, ML frameworks, and strong programming skills. With a competitive salary, this is an opportunity to impact cutting-edge AI technology in a rapidly growing company.

Benefits

Competitive salary

Stock options

Location incentive for commuting

Qualifications

• 5+ years of experience in HPC, HFT, large-scale simulation, or AI infrastructure.
• Hands-on experience with ML compilers and runtime optimisations.
• Strong debugging and performance-tuning capabilities.

Responsibilities

• Design and build systems for AI/ML workloads across distributed clusters.
• Optimise for low-latency and real-time inference.
• Collaborate with hardware teams to maximise OTPU capabilities.

Skills

C++

Python

Distributed Systems

HPC

Real-time Data Processing

ML Compilers

Performance Tuning

Education

Degree in Computer Science

Degree in Engineering

Degree in Mathematics

Tools

LLVM

MLIR

PyTorch

ONNX

OpenXLA

Job description

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Senior / Staff Software Engineer (AI / Compiler), luton, bedfordshire

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Client:

Location:

luton, bedfordshire, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

5

Posted:

31.05.2025

Expiry Date:

15.07.2025

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Job Description:

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.