At a Glance
- Tasks: Join a research team to innovate in image and video generation for AI navigation and planning.
- Company: Leading tech company with a focus on cutting-edge AI research and commercialization.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a strong track record of impactful research.
- Why this job: Be at the forefront of AI technology and contribute to groundbreaking projects.
- Qualifications: Experience in generative models, reinforcement learning, and robot navigation is preferred.
The predicted salary is between 60000 - 80000 € per year.
Image and video generation for world model navigation, interaction and planning. You'd be joining a research team that focuses mostly on commercialization and demo with end-to-end ownership. The team has a strong track record on a wide range of applications from audio to image and video generation, and on-device and server deployments, with publications in top venues such as ICML, CVPR, ICCV, etc. We're expanding into PhysicalAI and world models for navigation, interaction and planning, and we are interested in candidates with the following experiences:
- Generative models
- Diffusion/flow Model/architectural efficiency
- Reinforcement learning
- Robot navigation
- Planning and simulation
- Physical demos
ML Research Scientist (GenAI) in Cambridge employer: microTECH Global LTD
As a leading innovator in the field of AI research, our company offers an exceptional work environment that fosters creativity and collaboration. Located in a vibrant tech hub, we provide our ML Research Scientists with access to cutting-edge resources, opportunities for professional development, and a culture that values diversity and inclusion. Join us to be part of a team that not only pushes the boundaries of technology but also prioritises employee growth and well-being.
StudySmarter Expert Advice🤫
We think this is how you could land ML Research Scientist (GenAI) in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who are already working in ML or GenAI. Attend meetups, webinars, or conferences where you can chat with potential colleagues and learn about their experiences.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects related to generative models, reinforcement learning, or any relevant demos. This is your chance to demonstrate your expertise and creativity in a tangible way.
✨Tip Number 3
Prepare for interviews by brushing up on key concepts in ML and GenAI. Be ready to discuss your past work and how it relates to the role. Practise explaining complex ideas simply – it shows you really understand your stuff!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace ML Research Scientist (GenAI) in Cambridge
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in generative models and reinforcement learning. We want to see how your skills align with our focus on image and video generation, so don’t hold back!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and how your background fits into our mission at StudySmarter. Be specific about your experiences with planning and simulation.
Showcase Your Projects:If you've worked on any cool projects related to robot navigation or physical demos, make sure to mention them! We love seeing practical applications of your skills, especially if they’ve led to publications.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensures you’re considered for this exciting role in our research team!
How to prepare for a job interview at microTECH Global LTD
✨Know Your Generative Models
Make sure you brush up on your knowledge of generative models, especially diffusion and flow models. Be ready to discuss their applications in image and video generation, as well as how they relate to the role's focus on world model navigation.
✨Showcase Your Research Experience
Prepare to talk about your previous research projects, particularly those that have led to publications in top venues like ICML or CVPR. Highlight any experience you have with reinforcement learning and robot navigation, as these are key areas for the team.
✨Demonstrate Problem-Solving Skills
Think of examples where you've tackled complex problems in planning and simulation. Be ready to explain your thought process and how you approached these challenges, as this will show your analytical skills and creativity.
✨Engage with PhysicalAI Concepts
Familiarise yourself with the latest trends in PhysicalAI and how they can be applied to navigation and interaction. Showing genuine interest and understanding in this area will set you apart and demonstrate your enthusiasm for the role.
