Member of Technical Staff - Post-Training in London

Member of Technical Staff - Post-Training in London

London Full-Time 30000 - 40000 £ / year (est.) On-site
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At a Glance

  • Tasks: Build systems that transform powerful AI models into aligned agents and drive innovative research.
  • Company: Join Reflection AI, a cutting-edge team from top tech companies.
  • Benefits: Top-tier salary, comprehensive health benefits, and generous parental leave.
  • Other info: Dynamic startup environment with opportunities for career growth and collaboration.
  • Why this job: Make a real impact in AI and shape the future of open intelligence.
  • Qualifications: Deep understanding of machine learning and strong engineering skills required.

The predicted salary is between 30000 - 40000 £ per year.

Join to apply for the Member of Technical Staff - Post-Training role at Reflection AI.

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

  • Build systems that transform powerful pre-trained models into aligned and general agents.
  • Drive research and engineering initiatives that push the frontier of post-training, from data curation to large-scale optimization.
  • Develop data generation pipelines, reward models, reinforcement learning algorithms, and inference-time scaling techniques.
  • Collaborate across pre-training and post-training teams to deliver step-function gains in model capability.
  • Contribute to shaping our understanding of how large models learn to reason, follow instructions, and improve through reinforcement learning.

About You

  • Deep understanding of machine learning fundamentals and practical experience with large-scale LLM training.
  • Strong engineering skills, comfortable diving into complex ML codebases and distributed systems.
  • Experience improving model behavior through data, reward modeling, or RL techniques.
  • Evidence of owning ambitious research or engineering agendas that led to measurable model improvements.
  • Thrive in a fast-paced, high-agency startup environment; bias toward action and clarity of execution.
  • Able to work fluidly across research and infra boundaries.
  • Strong communication capabilities and comfort working collaboratively.
  • Passionate about advancing the frontier of intelligence.

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.

Seniority level: Entry level

Employment type: Full-time

Job function: Engineering and Information Technology

Industries: Software Development

Member of Technical Staff - Post-Training in London employer: Reflection AI

At Reflection, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through our mentorship opportunities and the chance to lead a talented team in a fast-paced environment, all while enjoying top-tier benefits such as unlimited paid time off and comprehensive health coverage. Located in a vibrant area, we offer a unique opportunity to contribute to groundbreaking AI research while ensuring a supportive work-life balance.

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Contact Details:

Reflection AI Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Member of Technical Staff - Post-Training 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 AI 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 AI.

✨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 AI.

✨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 AI 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 - Post-Training in London

Machine Learning Fundamentals
Large-Scale LLM Training
Engineering Skills
Complex ML Codebases
Distributed Systems
Data Curation
Reward Modeling

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 AI.

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 AI 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 AI

✨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 AI 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.