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AI Accelerator Product Systems Engineer

Lumai -
Oxford

Quick apply

Job details

Full-time

Benefits

Cycle to work scheme
Annual leave
Company pension
Private medical insurance

Qualifications

Technical troubleshooting
Software deployment
Technical support
Analysis skills
Equipment installation and commissioning
Computer hardware
Systems engineering
AI

Full job description

The Opportunity

Lumai is redefining how the world computes. We are an ambitious, venture-backed UK startup pioneering a breakthrough AI accelerator for data centers which uses 3D optical compute. Our radical technology uses light to perform computation at orders of magnitude faster speeds and at far greater scales than ever before, all whilst consuming far less energy than traditional approaches.

Lumai is unlocking performance and efficiency gains that could transform the economics of AI and compute infrastructure and reshape how intelligence scales globally.

If you are passionate about bringing groundbreaking technology to market, and want to be part of a team pushing the boundaries of what is physically possible, Lumai is where you can make it happen.

About Lumai

Founded in 2022, Lumai is a University of Oxford spinout using optical processing to accelerate large language models (LLMs) and other transformer-based AI systems. The team combines expertise in optical computing, machine learning, and physics.

Lumai has already secured over $15 million in investment from leading deep-tech investors like Constructor Capital, IP Group, PhotonVentures and government grants, and is scaling rapidly to deploy the fastest optical compute currently available globally.

The Role

We are bringing the world's first optical AI compute platform to market. As we move from development into field deployment, we are looking for a Product Systems Engineer to own the hands-on technical delivery of Iris servers - from integration and bring-up inside our engineering team through to deployment and live operation in third-party data centre environments.

You will begin by working directly alongside our core engineering team – owning the integration and validation of Lumai Iris server units. This is intentional: the best way to develop deep expertise in a novel platform is to build it. As deployments go live, you will take ownership in the field - leading system bring-up, performance characterisation, and post-deployment support, and acting as the primary technical contact for data centre operators and end customers.

This is an opportunity to work at the cutting edge of efficient AI inference - deploying a genuinely novel compute platform into production for the first time, and playing a central role in how it reaches the world.

What You'll Do

Integrate and build Lumai Iris server units alongside the engineering team - owning bring-up, validation, and performance characterisation of units ahead of deployment
Lead system bring-up, validation, and performance characterisation of deployed units in third-party data centre environments
Own on-site and remote troubleshooting of hardware issues, acting as the first line of response post-deployment
Train and enable data centre operators and customer engineering teams on the Iris platform
Act as the primary post-deployment technical contact for customers and data centre operators
Feed field findings, deployment issues, and customer feedback back into product and engineering

What We're Looking For

Must-Have

Hands-on experience in a systems engineering, field engineering, or hardware deployment role within AI infrastructure, HPC, or comparable hardware
Practical experience with system integration, bring-up, and hardware-level troubleshooting
Familiarity with data centre environments - rack power, thermal, and networking
Comfortable in a customer-facing role, able to communicate clearly with operators and engineering teams alike
Comfortable working in a fast-moving, early-stage environment where the product and the deployment playbook are both still being developed

Strong Preference For

Experience with AI inference hardware or accelerated compute systems
Enough performance analysis experience to characterise results and explain them to customer teams
Genuine curiosity in, novel compute architectures - post-silicon approaches
Programming literacy (for example Python) sufficient to engage credibly on benchmark methodology and basic automation
Experience in a deep-tech, semiconductor, or hardware startup environment

Compensation & Benefits

Highly Competitive Salary: We are not saying our salary is a blank check, but let's just say it won't be a source of your stress
Share Option Scheme: We are all in this together! We believe in shared success while we build the Lumai of tomorrow
Pension Scheme: Plan for retirement with AVIVA
Private Health Insurance: We firmly believe that you come first, and a happy you is a healthy you! Look after yourself and your loved ones with AXA
Cycle to Work: Spread the cost of a bike, a bike and accessories or just accessories and save on tax
L&D Allowance: Stay at the forefront of your field with a £500 annual development budget
Subsidised On-site Lunches: Enjoy on-site healthy meals at half the price, as Lumai covers 50% of the cost
Holidays: Enjoy some deserved "me time" with 25 days paid holiday (plus bank holidays) per year
Socials: Be part of an inclusive community enjoying occasional all-company off-sites, lunches and socials

Interview Process

Our process is four stages. An initial conversation with our HR team to understand what you want from the role and what we want from it. Two technical sessions with our Product and Leadership team. Finally, an HR-team session covering scope, terms, and any final questions. We aim to move fast on candidates we are excited about; expect roughly three to four weeks end to end.

Lumai is an equal opportunity employer. We make hiring decisions on merit, scope-fit, and the strength of the working relationship we expect to build with each hire. Applications welcome from candidates of any background. If you are not sure whether you are a fit, send a note anyway.

Quick apply

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