Research Software Engineer - ML Training Infrastructure

Research Software Engineer - ML Training Infrastructure

Full-Time 59400 - 72600 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Architect and optimise AI training infrastructure for scalable systems.
  • Company: Reflection, a leading UK tech company focused on AI innovation.
  • Benefits: Top-tier salary, comprehensive health benefits, and a supportive work environment.
  • Other info: Dynamic role with opportunities for professional growth.
  • Why this job: Join a cutting-edge team and shape the future of AI technology.
  • Qualifications: Experience in distributed systems and tools like PyTorch and JAX.

The predicted salary is between 59400 - 72600 £ per year.

Reflection, based in the United Kingdom, is seeking a Software Engineer to architect and optimize the training infrastructure for AI models.

The role focuses on building scalable systems for reinforcement learning and distributed training, requiring deep experience in distributed systems.

Candidates should have practical skills in tools like Py Torch and JAX, and a robust understanding of performance optimization.

The position offers top-tier compensation and comprehensive health benefits, alongside a supportive work environment. #J-18808-Ljbffr

Research Software Engineer - ML Training Infrastructure employer: Reflection

At Reflection, we are committed to fostering a dynamic and inclusive work environment where innovation thrives. As a Member of Technical Staff - Data Ingestion Engineer, you will be part of a small, talent-dense team dedicated to building open superintelligence, with access to top-tier compensation, comprehensive health benefits, and generous parental leave. Our culture prioritises collaboration and personal growth, ensuring that you can make a meaningful impact while enjoying a supportive work-life balance in a cutting-edge field.

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Contact Details:

Reflection Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Software Engineer - ML Training Infrastructure

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 Research Software Engineer - ML Training Infrastructure

Software Engineering
Architecting Systems
Optimising Training Infrastructure
Distributed Systems
Reinforcement Learning
Distributed Training
PyTorch

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.