At a Glance
- Tasks: Design and build systems for managing large-scale GPU infrastructure supporting ChatGPT.
- Company: Join a leading AI company at the forefront of technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make a real impact on AI infrastructure and enhance developer productivity.
- Qualifications: 5+ years in software engineering with experience in GPU or compute infrastructure.
The predicted salary is between 80000 - 100000 £ per year.
About the Team
Chat GPT Engineering builds and operates the compute platform powering one of the world's largest AI products.
Every Chat GPT conversation relies on massive GPU clusters serving inference workloads with high reliability, efficiency, and performance.
As our GPU fleet continues to grow, we're investing in the infrastructure that operates it.
Our team builds the tooling, automation, and intelligent systems that make GPU infrastructure scalable, observable, and increasingly autonomous.
We work across production engineering, distributed systems, capacity management, and AI‑powered operational tooling to help researchers and product teams move faster while maximizing efficiency of every GPU.
This is a unique opportunity to work on infrastructure at the frontier of AI, where small improvements in fleet efficiency, reliability, and automation have an outsized impact on the development and deployment of AGI.
About the Role
We're looking for a Software Engineer with deep experience operating large‑scale GPU or compute infrastructure.
You'll design and build the systems that manage GPU clusters at scale—from fleet health and capacity planning to operational automation and intelligent agents that reduce manual intervention.
You'll partner closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and overall compute utilization.
This role is ideal for engineers who enjoy solving complex operational challenges, building internal platforms, and working on infrastructure that directly powers frontier AI.
- In This Role, You Will
- Design, build, and operate software that manages large‑scale GPU infrastructure supporting Chat GPT inference.
- Build internal platforms, tooling, and AI‑powered agents that automate fleet operations and reduce operational overhead.
- Improve observability, reliability, and operational efficiency across thousands of GPUs.
- Develop systems for capacity planning, scheduling, fleet health monitoring, and incident response.
- Identify infrastructure bottlenecks and implement solutions that improve utilization, scalability, and performance.
- Partner closely with research, platform, networking, and systems teams to continuously improve our compute platform.
- Help establish engineering best practices around operational excellence, automation, and infrastructure reliability.
- You Might Thrive in This Role If You
- Have experience operating large‑scale production infrastructure, preferably GPU clusters or other compute‑intensive distributed systems.
- Have a background in Production Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Platform Engineering.
- Have built software that automates operational workflows rather than relying on manual processes.
- Have experience with Kubernetes, Linux systems, container orchestration, or distributed infrastructure.
- Understand infrastructure observability, monitoring, capacity planning, and incident management.
- Enjoy identifying cross‑team pain points and building reusable platforms that improve developer productivity.
- Are comfortable working across software engineering and systems operations, owning problems end‑to‑end.
- Thrive in fast‑moving environments with significant technical ambiguity.
Qualifications
- 5+ years of software engineering experience building production infrastructure.
- Strong programming skills in Go, Python, C++, Rust, or similar systems languages.
- Experience designing and operating highly available distributed systems.
- Experience with GPU infrastructure, high‑performance computing, ML infrastructure, or large‑scale compute platforms.
- Experience with Kubernetes, cloud infrastructure, Linux, networking, and observability tooling.
- Excellent debugging, systems design, and operational problem‑solving skills.
- Strong communication skills and experience collaborating across engineering organizations.
EEO Statement
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
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Software Engineer, GPU Infrastructure- ChatGPT Engineering in London employer: The Consulting Solutions
Elastic is an exceptional employer that fosters a culture of innovation and inclusivity, making it an ideal place for a Senior Solutions Architect to thrive. With competitive salaries, flexible working arrangements, and a strong commitment to employee development, you will have the opportunity to grow your technical and sales skills while making a meaningful impact in the enterprise sector. Additionally, our generous benefits, including health coverage and paid volunteer time, reflect our dedication to supporting our employees both personally and professionally.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer, GPU Infrastructure- ChatGPT Engineering in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at The Consulting Solutions or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Tap into Online Developer Communities
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We think you need these skills to ace Software Engineer, GPU Infrastructure- ChatGPT Engineering in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at The Consulting Solutions.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at The Consulting Solutions and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at The Consulting Solutions
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If The Consulting Solutions uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
