At a Glance
- Tasks: Conduct cutting-edge research in machine learning and develop innovative solutions for real-world applications.
- Company: Join a leading tech firm at the forefront of AI research.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on innovation and creativity.
- Why this job: Make a significant impact in the AI field while working with top-tier researchers.
- Qualifications: PhD in CS/EE or relevant experience; strong skills in ML frameworks and Python.
The predicted salary is between 60000 - 84000 £ per year.
Education and experience:
- PhD in CS/EE or related research experience in academia or industry
- We will consider various levels of experience in relevant research areas
Key Skills:
- Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.)
- Experience with deployment on embedded/mobile devices (such as smartphones, with mobile CPU, GPU, NPU)
- Experience with distributed and multi-GPU training at scale
- Fluency in Python, C/C++ and GNU Linux
- Proficiency in code version control, Git and GitHub
- Experience in working as a member of a team
- Solid publication record of papers in top-tier venues, such as NeurIPS/ICLR/ICML/MobiCom/MobiSys/ICCAD/MLSys
Any of the following skills will also be positively considered:
- Experience in real-world mobile system deployment
- Research experience in efficient Generative AI, including language, visual or multimodal tasks. This includes different aspects of the pipeline, from data and preprocessing to large model adaptation, fine-tuning and on-device optimization.
- Android operating system and Android app development
We think you need these skills to ace ML Research Scientist
Machine Learning Frameworks (PyTorch, TensorFlow, JAX)
Efficient Machine Learning (quantization, pruning, sparsification, distillation)
Deployment on Embedded/Mobile Devices
Distributed and Multi-GPU Training
Fluency in Python
Fluency in C/C++
GNU Linux Proficiency
