Director of GenAI Foundation Models
AMD
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Job Description
Director of GenAI Foundation Models
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
The Role
We are seeking a Director of GenAI Foundation Models to build and lead our AI Modeling team.
The Person
The ideal candidate will have a proven track record of building and leading a world-class research and engineering team focused on LLMs and foundation models, with a strong publication record in top-tier research venues. Experience with the latest state-of-the-art foundation models—especially in the areas of LLMs and multimodality models—is essential. Deep knowledge in pretraining, SFT, reinforcement learning, and current research trends is also required. We are looking for a leader with hands-on expertise in training large foundation models at scale.
Key Responsibilities
- Set the vision and strategy for developing large foundation models across various domains, such as natural language, computer vision, and multimodal data.
- Lead a team of researchers and engineers working on cutting-edge techniques for pretraining, fine-tuning, RL, evaluating, and deploying large foundation models at scale.
- Collaborate with cross-functional teams and stakeholders to identify opportunities and enhance the platforms and infrastructure supporting large-scale model development.
- Communicate the results, capabilities, and impact of foundation models and AI to both internal and external audiences.
- Establish best practices and standards to ensure the quality, reliability, fairness, and ethical use of AI and large foundation models.
Preferred Experience
- Proven experience leading a research team in machine learning or a related field.
- Deep technical expertise in natural language processing and generative AI.
- A strong publication record in top-tier conferences and journals related to machine learning.
- Exceptional leadership skills and the ability to work collaboratively with cross-functional teams and customers.
- Excellent communication skills—written, verbal, and presentation.
- A demonstrated ability to mentor, coach, and inspire a diverse and talented team of researchers and engineers.
Academic Credentials
A PhD (or a master’s degree with equivalent experience) in artificial intelligence, machine learning, computer science, or a related field.
Key skills/competency
- Generative AI
- Large Language Models (LLMs)
- Foundation Models
- Machine Learning Research
- Natural Language Processing (NLP)
- Computer Vision
- Reinforcement Learning
- Model Pretraining & Fine-tuning
- Large-scale Model Training
- AI Ethics & Fairness
How to Get Hired at AMD
- Research AMD's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Customize your resume: Tailor your Director of GenAI Foundation Models resume to highlight experience in LLMs, foundation models, and AI leadership, aligning with AMD's innovation focus.
- Showcase technical depth: Prepare to discuss hands-on expertise in large-scale model training, pretraining, SFT, and reinforcement learning relevant to AMD's AI initiatives.
- Emphasize leadership and collaboration: During interviews, demonstrate your ability to lead research teams, set technical vision, and collaborate cross-functionally within a complex organization like AMD.
- Highlight publication impact: Be ready to discuss your strong publication record in machine learning conferences and journals, showcasing your contributions to the field and fit for AMD's research-driven environment.
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