Applied Research Scientist - AI Models

Job Description

THE ROLE: T he AI Models team is looking for exceptional machine learning scientists and engineers to explore and innovate on training and inference techniques for large language models (LLMs), large multimodal models (LMMs), image/video generation and other foundation models . You will be part of a world-class research and development team focussing on efficient and scalable pre-training, instruction tuning, alignment and optimization . As an early member of the team, you can help us shap e the direction and strategy to fulfill this important charter. THE PERSON: This role is for you if you are passionate about reading through the latest literature, coming up with novel ideas, and implementing those through high quality code to push the boundaries on scale and performance. The ideal candidate will have both theoretical expertise and hands-on experience with developing LLMs, LMMs, and/or diffusion models. We are looking for someone who is familiar with hyper-parameter tuning methods, data preprocessing & encoding techniques and distributed training approaches for large models. KEY RESPONSIBILITIES: Pre-train and post-train models over large GPU clusters while optimizing for various trade-offs . Improve upon the state-of-the- art in G enerat ive AI model architectures, data and training techniques. Accelerate the training and inference speed across AMD accelerators . Build agentic frameworks to solve various kinds of problems Publish your research at top-tier conferences, workshops and/ or through technical blogs. Engage with academia and open-source ML communities. Drive continuous improvement of infrastructure and development ecosystem. PREFERRED EXPERIENCE: Strong development and debugging skills in Python. Experience in deep learning frameworks ( like PyTorch or TensorFlow ) and distributed training tools (like DeepSpeed or Pytorch Distributed ) . Experience with fine-tuning methods (like RLHF & DPO) as well as parameter efficient techniques (like LoRA & DoRA). Solid understanding o f various types of transformer s and state space models . Strong publication record in top-tier conferences, workshops or journals. S olid communication and problem-solving skills. Passionate about learning new stuffs in this domain as well as innovating on top of it ACADEMIC CREDENTIALS: Advanced degree ( Master s or PhD) in machine learning, computer science, artificial intelligence, or a related field is expected. Exceptional Bachelor s degree candidates may also be considered . #LI-MK1 Benefits offered are described: AMD benefits at a glance .