At a Glance
- Tasks: Design and operate large-scale GPU infrastructure for cutting-edge AI model training and inference.
- Company: Join a leading tech firm focused on innovative AI solutions.
- Benefits: Top-tier salary, comprehensive health benefits, and generous parental leave.
- Other info: Enjoy daily meals, team celebrations, and a supportive work culture.
- Why this job: Make an impact in AI by optimising performance and building next-gen systems.
- Qualifications: Experience with large-scale GPU systems and modern inference frameworks required.
The predicted salary is between 56700 - 69300 £ per year.
About The Role
- Design, build, and operate large-scale GPU infrastructure for high-throughput model inference and mid-training workloads.
- Develop systems that power synthetic data generation and reinforcement learning pipelines at scale.
- Build high-performance inference platforms capable of serving and evaluating models across thousands of GPUs.
- Optimize throughput, latency, and GPU utilization for large language model inference and rollout workloads.
- Build infrastructure that supports reinforcement learning pipelines, including large-scale rollout generation, evaluation, and policy improvement loops.
- Work closely with research teams to support distributed RL workloads and large-scale model evaluation infrastructure.
- Improve performance of model execution through kernel-level optimization, model parallelism strategies, and GPU runtime improvements.
- Develop distributed systems that enable large-scale synthetic data generation and RL-driven training workflows.
- Diagnose and resolve performance bottlenecks across inference runtimes, GPU kernels, networking, and distributed compute systems.
- Ideal Experience
- Experience deploying and operating large-scale GPU systems for inference or model serving.
- Several years of hands-on experience building and running production infrastructure.
- Strong understanding of GPU performance characteristics and optimization techniques.
- Experience working with modern inference frameworks such as SGLang, Megatron, or similar high-performance LLM runtimes.
- Familiarity with distributed reinforcement learning infrastructure or rollout generation systems.
- Experience optimizing throughput for large-scale model execution workloads.
- Experience working with GPU kernels or low-level performance optimization.
- Familiarity with infrastructure used for synthetic data pipelines or RL training workflows.
- Experience debugging performance issues across GPU, networking, and distributed execution layers.
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.
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Member of Technical Staff - Mid-Training Infra in London employer: Reflection
At Reflection, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the rapidly evolving field of AI. Our inclusive work culture fosters personal and professional growth, offering top-tier compensation, comprehensive health benefits, and unlimited paid time off to ensure a healthy work-life balance. Join us in shaping the future of open foundational models while enjoying unique perks like daily meals and generous parental leave policies, all within a dynamic and supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff - Mid-Training Infra 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 Reflection 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
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Reflection.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Reflection.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Reflection that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Member of Technical Staff - Mid-Training Infra 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 Reflection.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Reflection 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 Reflection
✨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 Reflection 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.
