Senior AI ML Lead

WHAT YOU DO AT AMD CHANGES EVERYTHING

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

Senior AI/ML Lead :

The Senior AI/ML Engineer leads the design, development, deployment, and optimization of machine learning and AI solutions at scale. This role requires deep technical expertise in ML/AI algorithms, data engineering, model lifecycle management, and production readiness. The engineer collaborates with data scientists, software engineers, product managers, and business stakeholders to drive end-to-end AI initiatives.

The Person

Youre a highly motivated team player with a strong development background, problem solving mentality, excellent communication skills, ability to prioritize tasks along with willingness to learn and adapt. Excellent teamwork skills and capable of working independently.

Key Responsibilities

10+ years of experience in machine learning or AI engineering.

• Strong programming skills: Python (primary), plus experience with Java/Scala/Go is a plus.
• Expert knowledge of ML frameworks: PyTorch, TensorFlow, Scikit-learn.
• Hands-on experience with NLP, LLMs, deep learning, or computer vision.
• Experience deploying ML models in production at scale.
• Strong understanding of distributed systems, data pipelines, and cloud infrastructure.
• Experience with MLOps tools: MLflow, Kubeflow, Airflow, Vertex AI, SageMaker, Azure ML.
• Familiarity with vector databases, RAG systems, and fine-tuning LLMs.
• Strong knowledge of data structures, algorithms, and software engineering principles.
• Experience with Docker, Kubernetes, CI/CD pipelines.
  
  
  

• Experience with large-scale training using GPUs/TPUs.
• Knowledge of model compression, quantization, and optimization frameworks (TensorRT, ONNX).
• Experience with streaming systems (Kafka, Kinesis, Pub/Sub).
• Previous experience in big data ecosystems: Spark, Hadoop, Databricks.
• Background in designing secure, compliant AI systems (privacy, governance, responsible AI).
• Contributions to open-source ML/AI projects. 
  
  
  

• Bachelor’s/Master’s degree in Computer Science or related field strongly preferred