ADVANCE YOUR CAREER. ADVANCE THE WORLD.
At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And we’re looking for talent who feel the same: people who want to leave the planet better than they found it, those who don’t shy away from humanity’s challenges but are determined to help solve them.
AMD is powering the next generation of supercomputing, high-performance computing, cloud, and AI. Whether you’re designing next-gen processors, enabling AI breakthroughs, or creating go-to-market plans, every role at AMD contributes to something bigger — technology that moves the world forward.
Lead Machine Learning Engineer
AMD is seeking talented Machine Learning Engineers to join our AI/ML Solutions Team in Hyderabad. In this role, you will help deliver end-to-end AI/ML solutions by working with state-of-the-art neural network architectures—including Vision(CNN), Vision Transformers (ViTs), LLMs, BERT, Transformers,
and custom models—and optimizing them for AMD's next-generation compute platforms.
You will be involved in compiler development, performance analysis, compiler optimization, software framework development, and system-level engineering. Working in a highly collaborative R&D; environment, you will partner with hardware and software engineering teams, application experts, and customers to enable high-performance AI solutions across a range of AMD technologies.
This is an excellent chance to contribute to cutting-edge AI innovation while growing your expertise in machine learning, systems engineering, and product development.
Key Responsibilities
Work with state-of-the-art AI/ML compiler toolchains across front-end, back-end, optimization, performance, and debugging domains.
Collaborate with the AI/ML Solutions team to accelerate solution development and deployment.
Evaluate and optimize industry-standard and custom neural network arc
📌 Lead Machine Learning Engineer (Hyderabad)
🏢 AMD
📍 Hyderabad