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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 48000 - 72000 £ 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 Machine Learning Researcher employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Researcher
✨Tip Number 1
Network like a pro! Reach out to people in the AI and machine learning community, especially those who work with RLHF and generative models. Attend meetups, webinars, or conferences to make 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. This could be anything from GitHub repositories to blog posts explaining your research. It’s a great way to demonstrate your expertise beyond just your CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past projects and how they relate to the role. Practising common interview questions in AI can give you the edge you need.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you. Make sure your application stands out by tailoring it to highlight your experience with RLHF and generative models.
We think you need these skills to ace Senior Machine Learning Researcher
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 and 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. Let us know what excites you about working with RLHF and generative models.
Showcase Your Research: If you’ve published papers or contributed to open-source projects, make sure to include them in your application. We love seeing your work in top-tier conferences like NeurIPS or ICML, as it shows your commitment to the field!
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 from us!
How to prepare for a job interview at Microtech Global Ltd
✨Know Your Algorithms
Make sure you brush up on the latest developments in Reinforcement Learning and Generative AI. Be ready to discuss specific algorithms you've worked with, like policy gradients or actor-critic methods, and how they can be applied to align generative models with human preferences.
✨Showcase Your Research
Prepare to talk about your publications and any relevant projects you've contributed to. Highlight your experience at top-tier conferences like NeurIPS or ICML, and be ready to explain how your research aligns with the company's goals in AI.
✨Demonstrate Collaboration Skills
Since this role involves working closely with researchers and engineers, think of examples where you've successfully collaborated on projects. Discuss how you’ve built alignment pipelines or worked with human feedback teams to enhance model performance.
✨Get Hands-On with Tools
Familiarise yourself with deep learning frameworks like PyTorch, JAX, or TensorFlow. Be prepared to discuss your hands-on experience with training and fine-tuning generative models, and maybe even share some insights on large-scale distributed training on GPUs or TPUs.
