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- Tasks: Design and optimise algorithms for AI models that align with human preferences.
- Company: Leading AI research firm based in Cambridge or London.
- Benefits: Hybrid working, competitive salary, and opportunities for publishing research.
- Other info: Collaborative environment with chances to publish in top-tier AI conferences.
- Why this job: Join the forefront of AI innovation and make a real impact on future technologies.
- Qualifications: PhD in relevant field and expertise in Reinforcement Learning and deep learning frameworks.
The predicted salary is between 60000 - 80000 £ per year.
This is a permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs across multiple modalities. You’ll sit at the intersection of RL, LLMs, and generative modelling, helping us build the next generation of foundation models.
Responsibilities
- Develop and refine RLHF algorithms for large language and generative models.
- Research and implement deep reinforcement learning methods (policy gradients, actor‑critic, off‑policy learning) for model alignment.
- Train, fine‑tune, and evaluate LLMs and diffusion models at scale.
- Design experiments to align generative outputs with human and organisational preferences.
- Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines.
- Publish findings in top‑tier AI conferences and contribute to open‑source frameworks.
Key Requirements
- PhD in Computer Science, Machine Learning, or related field.
- Publications at NeurIPS, ICML, ICLR, ACL, or related venues.
- Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF).
- Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow).
- Proficiency in Python and standard ML libraries.
- Solid foundations in probability, optimisation, and statistics.
- Experience working with large‑scale distributed training on GPUs/TPUs.
If this sounds of interest, please reach out to daniel@microtech-global.com.
Artificial Intelligence Researcher employer: microTECH Global LTD
Contact Detail:
microTECH Global LTD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Researcher
✨Tip Number 1
Network like a pro! Reach out to fellow researchers and professionals in AI, especially those who have experience with RLHF and generative models. Attend meetups or conferences where you can chat about your work and interests – it’s all about making connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to reinforcement learning and generative AI. Whether it's GitHub repos or published papers, having tangible evidence of your expertise can really set you apart when you're chatting with potential employers.
✨Tip Number 3
Don’t just apply – engage! When you find a role that excites you, reach out directly to the hiring manager or team members on LinkedIn. Ask insightful questions about the role or the company’s projects. This shows genuine interest and can help you stand out from the crowd.
✨Tip Number 4
Keep it real with your online presence. Make sure your LinkedIn profile is up-to-date and reflects your passion for AI research. Share articles, insights, or even your thoughts on recent developments in RLHF. This not only showcases your knowledge but also keeps you on the radar of recruiters looking for talent like us!
We think you need these skills to ace Artificial Intelligence Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Reinforcement Learning and Generative AI. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or publications!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI research and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Research: If you've published papers at top-tier conferences like NeurIPS or ICML, make sure to mention them! We’re keen on seeing your contributions to the field, so include links or references to your work.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at microTECH Global LTD
✨Know Your Algorithms
Make sure you brush up on your knowledge of RLHF algorithms and deep reinforcement learning methods. Be ready to discuss specific techniques like policy gradients and actor-critic methods, as well as how you've applied them in past projects.
✨Showcase Your Research
Prepare to talk about your publications and any relevant research you've conducted. Highlight your contributions to top-tier AI conferences and how they relate to the role. This will demonstrate your expertise and commitment to the field.
✨Demonstrate Collaboration Skills
Since this role involves working with various teams, be prepared to share examples of how you've successfully collaborated with researchers and engineers in the past. Discuss any experiences where you’ve built alignment pipelines or worked on open-source frameworks.
✨Practice Problem-Solving
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when designing experiments or optimising algorithms. This will show your analytical abilities and how you approach complex challenges.