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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 the forefront of AI innovation and make a real impact on technology.
- 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 48000 - 72000 £ per year.
Job Description
Job Title: AI Researcher
Location: Cambridge or London, UK
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
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 people in the AI field, especially those who work with RLHF and generative models. Attend meetups or webinars, and don’t be shy to slide into DMs on LinkedIn – 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 related to reinforcement learning and generative AI. Whether it’s GitHub repos or blog posts, let your work speak for itself. This can really set you apart when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of deep learning frameworks and algorithms. Practice explaining complex concepts in simple terms, as you might need to discuss your research or past projects. Mock interviews can help you get comfortable with this!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Artificial Intelligence Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Researcher role. Highlight your experience with Reinforcement Learning and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Don’t forget to mention any publications or projects that showcase your expertise.
Showcase Your Research Experience: Since we’re looking for someone with a strong research background, make sure to detail your PhD work and any publications. We love seeing candidates who have contributed to top-tier conferences like NeurIPS or ICML!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy!
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 researchers, engineers, or feedback teams to achieve common goals, especially in building scalable alignment pipelines.
✨Get Hands-On with Tools
Familiarise yourself with the deep learning frameworks mentioned in the job description, like PyTorch and TensorFlow. If possible, bring examples of projects where you've trained or fine-tuned generative models, showcasing your practical experience and technical skills.
