At a Glance
- Tasks: Design and optimise software for large-scale machine learning workloads across supercomputers.
- Company: Join OpenAI, a leader in AI research and deployment.
- Benefits: Hybrid work model, relocation assistance, and a focus on professional growth.
- Other info: Dynamic environment with opportunities for innovation and career advancement.
- Why this job: Work at the forefront of AI, tackling complex challenges and making a real impact.
- Qualifications: Experience in distributed systems, proficient in Python and Rust, and strong engineering skills.
The predicted salary is between 60000 - 80000 £ per year.
About the Team
Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI. Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs.
About the Role
As a Training Runtime: Process Management Engineer, you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning hundreds of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Rust, building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure. We’re looking for people who love optimizing an end-to-end platform, understanding high-performance architectures to maximize both local and distributed performance across our supercomputers. We’re looking for engineers excited by the rapid pace of responding to the dynamic and evolving needs of our training runtime and compute stack.
This role is based in London, UK. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
- Work across our Python and Rust stack
- Design, build, and maintain software to orchestrate and monitor machine learning workloads on our largest supercomputers
- Profile and optimize our software stack to support computation orchestration at frontier scale
- Improve reliability, observability, and fault tolerance for long-running jobs
- Debug complex distributed systems issues across large clusters
- Respond to the changing shapes and needs of the ML systems to enable our researchers
You might thrive in this role if you:
- Have experience developing distributed systems (not just operating them)
- Enjoy understanding how large systems behave and fail at scale
- Care deeply about performance, correctness, and reliability
- Have strong software engineering skills and are proficient in Python and Rust or another systems programming language (e.g. C++)
- Have solid Linux knowledge, and are comfortable with systems-level debugging, performance analysis, and memory profiling
- Are comfortable and experienced working and developing asynchronous and concurrent systems
- Like high-ownership environments with light process and strong engineering agency
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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.
Training: Process Management Engineer employer: Slope
OpenAI is an exceptional employer, offering a dynamic work environment in London that fosters innovation and collaboration. With a hybrid work model and a strong emphasis on employee growth, you will have the opportunity to tackle complex challenges at the forefront of AI development while enjoying a culture that values diverse perspectives and encourages high ownership. Join us to be part of a mission-driven team dedicated to ensuring that artificial intelligence benefits all of humanity.
StudySmarter Expert Advice🤫
We think this is how you could land Training: Process Management Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, conferences, or even online webinars. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to distributed systems or high-performance computing. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Rust and Python skills. Practice coding challenges and system design problems that relate to distributed systems. The more comfortable you are with these topics, the better you'll perform when it counts!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team and contributing to our mission.
We think you need these skills to ace Training: Process Management Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with distributed systems and performance optimisation. We want to see how your skills align with the role of a Process Management Engineer, so don’t hold back!
Show Off Your Technical Skills:Since we’re working primarily in Rust and Python, it’s crucial to showcase your proficiency in these languages. Include specific projects or experiences where you’ve used them to solve complex problems, especially in high-performance environments.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and enthusiasm for the role!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Slope
✨Know Your Tech Stack
Make sure you’re well-versed in both Python and Rust, as these are key to the role. Brush up on your knowledge of distributed systems and be ready to discuss how you've tackled performance and reliability challenges in past projects.
✨Understand the Big Picture
Familiarise yourself with the concepts of high-performance computing and how they relate to machine learning workloads. Be prepared to explain how you would optimise a system for scale and stability, showcasing your design judgement.
✨Prepare for Problem-Solving
Expect to face ambiguous problems during the interview. Think through potential scenarios where you might need to debug complex distributed systems issues and articulate your thought process clearly. Show them how you approach problem-solving!
✨Show Your Passion for AI
Demonstrate your enthusiasm for working at the frontier of AI development. Share any personal projects or experiences that highlight your commitment to optimising systems and advancing technology, as this will resonate well with the team’s goals.
