At a Glance
- Tasks: Design and build distributed systems for large-scale AI training workloads.
- Company: Join OpenAI, a leader in cutting-edge AI technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on performance and reliability.
- Why this job: Make a real impact on AI research with innovative technology.
- Qualifications: Experience in low-level software and understanding of distributed systems.
The predicted salary is between 60000 - 80000 £ per year.
About the Team
The Platform Systems team at OpenAI operates at the intersection of cutting‑edge AI and large‑scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom‑built supercomputers. Our team develops core model training software and works deep in the stack—spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform.
About the Role
As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large‑scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large‑scale debugging.
In This Role, You Will
- Design and build distributed failure detection, tracing, and profiling systems for large‑scale AI training jobs
- Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior
- Improve observability, reliability, and performance across OpenAI’s training platform
- Debug and resolve issues in complex, high‑throughput distributed systems
- Collaborate with systems, infrastructure, and research teams to evolve platform capabilities
- Extend and adapt failure detection systems or tracing systems to support new training paradigms and workloads
You Might Thrive in This Role If
- You care deeply about performance, stability, and observability in distributed systems
- Enjoy finding and fixing issues in large‑scale systems and automating operational workflows
- Have experience writing low‑level software where system details matter
- Understand hardware, operating systems, networking, concurrency, and distributed systems
- Have a background in high‑performance computing or low‑level systems engineering
- Are excited to work on critical infrastructure that powers frontier AI research
Equal Opportunity Employer
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.
Software Engineer, Platform Systems in London employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer, Platform Systems in London
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace Software Engineer, Platform Systems 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 Doist.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Doist 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 Doist
✨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 Doist 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.