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For Companies At a Glance
- Tasks: Design and operate large-scale GPU infrastructure for cutting-edge AI models.
- Company: Join a mission-driven team from top AI companies like DeepMind and OpenAI.
- Benefits: Top-tier salary, comprehensive health benefits, and generous parental leave.
- Why this job: Make a real impact in AI by building the future of open superintelligence.
- Qualifications: Experience in high-performance computing and strong GPU knowledge required.
- Other info: Dynamic startup environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
Our Mission Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.
About the Role
- Design, build, and operate Reflection’s large-scale GPU infrastructure powering pre-training, post-training, and inference.
- Develop reliable, high-performance systems for scheduling, orchestration, and observability across thousands of GPUs.
- Optimize cluster utilization, throughput, and cost efficiency while maintaining reliability at scale.
- Build tools and automation for distributed training, inference, monitoring, and experiment management.
- Collaborate closely with research, training, and platform teams to accelerate development and enable large-scale training and inference.
- Push the limits of hardware, networking, and software to accelerate the path from idea to model.
About You
- Deep systems or infrastructure engineering experience in high-performance or distributed computing environments.
- Strong understanding of GPUs, CUDA, NCCL, and large-scale training and inference frameworks and libraries (PyTorch, DeepSpeed, JAX, Megatron-LM, SGLang, vLLM, etc.).
- Hands-on experience with containerization, orchestration, and cluster management (Kubernetes, Slurm, or similar).
- Familiar with modern observability stacks and performance profiling tools.
- High agency and the ability to thrive in a fast-paced, high-ownership startup environment.
- Excited to build from zero to one defining how frontier-scale training/RL infrastructure is architected and operated.
- Motivated by enabling researchers and engineers to build the world’s most capable open-weight AI systems.
What We Offer:
- Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.
- Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.
- Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.
- Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time.
- Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.
Member of Technical Staff - GPU Infrastructure employer: Reflection AI, Inc.
Contact Detail:
Reflection AI, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Member of Technical Staff - GPU Infrastructure
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work at Reflection or similar companies. Use LinkedIn to connect and don’t be shy about asking for informational chats – it’s all about making those connections!
✨Tip Number 2
Show off your skills! If you’ve got projects or contributions to open-source that relate to GPU infrastructure or AI, make sure to highlight them. Create a portfolio or GitHub repo that showcases your work – it’s a great way to stand out!
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of GPUs, CUDA, and distributed systems. Practice coding challenges and system design questions that are relevant to the role. We want to see how you think and solve problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of our mission to build open superintelligence. Don’t miss out on this opportunity!
We think you need these skills to ace Member of Technical Staff - GPU Infrastructure
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with GPUs, CUDA, and large-scale training frameworks. We want to see how your skills align with our mission of building open superintelligence!
Showcase Your Projects: Include any relevant projects or experiences that demonstrate your hands-on work with distributed computing and cluster management. We love seeing real-world applications of your skills, so don’t hold back!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your passion for AI and infrastructure shines through without unnecessary fluff.
Apply Through Our Website: We encourage you to submit your application directly 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!
How to prepare for a job interview at Reflection AI, Inc.
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like GPUs, CUDA, and the various frameworks. Brush up on your knowledge of distributed computing and be ready to discuss how you've applied these in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in high-performance environments. Think about how you optimised systems or improved efficiency, and be ready to explain your thought process and the impact of your solutions.
✨Demonstrate Collaboration Experience
Since the role involves working closely with research and platform teams, be prepared to discuss your experience in collaborative projects. Highlight instances where you’ve successfully worked with cross-functional teams to achieve a common goal.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the company’s mission and the role. Inquire about their current projects, challenges they face in GPU infrastructure, or how they envision the future of open superintelligence. This shows you’re engaged and eager to contribute.
