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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.
- Why this job: Join a cutting-edge team shaping the future of AI with real-world impact.
- Qualifications: PhD in relevant field and expertise in Reinforcement Learning and generative models.
- Other info: Collaborative environment with chances to publish in top-tier conferences.
The predicted salary is between 36000 - 60000 £ 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).
- Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs).
- 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.
Senior Researcher, Machine Learning in England employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Researcher, Machine Learning in England
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and machine learning space. Attend meetups, webinars, or conferences where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to RLHF and generative models. Share your work on platforms like GitHub or even your own website. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with deep reinforcement learning and generative models. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role.
We think you need these skills to ace Senior Researcher, Machine Learning in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight 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 come through.
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 that demonstrate your expertise.
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’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
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 successful collaborations. Discuss how you've worked with engineers and human feedback teams to build scalable alignment pipelines or similar projects.
✨Familiarise Yourself with Tools
Ensure you're comfortable discussing the deep learning frameworks mentioned in the job description, like PyTorch, JAX, and TensorFlow. If you have experience with large-scale distributed training on GPUs/TPUs, be ready to explain your approach and any challenges you faced.
