Cambridge Residency Program - TaiX ML Residency
Microsoft, Newtown, Cambridge
Cambridge Residency Program - TaiX ML Residency
Salary not available. View on company website.
Microsoft, Newtown, Cambridge
- Full time
- Permanent
- Onsite working
Posted 2 days ago, 18 Dec | Get your application in today.
Closing date: Closing date not specified
job Ref: 62939aa40bd342f5a9122a7408d67df4
Full Job Description
- Undertake cutting-edge research in deepening our understanding of generative AI models, including the development of technical approaches to ensure they perform equally well in all scenarios.
- Write research code to develop and validate new approaches, or develop novel theoretical and practical insights.
- Collaborate with a diverse and multi-disciplinary team.
- Clearly communicate research ideas and results in writing, such as research papers, presentations, or research notes for internal and external audiences.
The Teachable AI Experiences (TaiX) (https://www.microsoft.com/en-us/research/project/taix/) team at Microsoft Research Cambridge (UK) is a multidisciplinary research group that brings together different skill sets to innovate human-AI interaction. The team is hiring a machine learning (ML) researcher to push the state-of-the-art of generative AI systems, with a goal of ensuring equitable experiences for all. The candidate should have deep technical knowledge of current generative AI models, with a particular focus on multi-modal models (e.g. image-text models like GPT-4Vision, LLaVa and CLIP). They should be able to approach technical problems in a multi-disciplinary way, and be passionate about building AI technologies that will ensure the inclusion of marginalised communities., PhD in Machine Learning, Deep Learning, or a related area. - Strong technical understanding of state-of-the-art generative AI models, with a particular focus of multi-modal models.
- Demonstrable ability to drive high-quality research insights through publications in top-tier machine learning conferences and journals (e.g. NeurIPS, ICML, ICLR, AAAI, ICCV, ECCV, CVPR, JMLR).
- Hands-on experience in implementing and empirically evaluating deep learning approaches in PyTorch.
- Effective communication skills and ability to work in a collaborative environment., Demonstrable research expertise in any of the following fields: AI fairness, AI interpretability and/or transparency, model adaption (e.g. PEFTs), data-centric AI, evaluation methods.
- The ability to approach technical problems and design solutions with a multi-disciplinary perspective.
- Passion for ensuring the inclusion of marginalised communities in AI technologies.
- Previous experience working in a multi-disciplinary team with diverse skill sets.
- Contribution to open-source code projects (e.g. on GitHub).