Senior ML Engineer - AI Labs

Job Requirements

About the Role

As a Senior Machine Learning Engineer within the Data & Analytics team, you will be responsible for managing and optimizing the training infrastructure for Large Language Models (LLMs). This role demands a deep understanding of GPU architecture, machine learning principles, and distributed computing. You will lead Gen AI initiatives in a cross-functional setup, ensuring efficient resource utilization and timely delivery of large-scale ML projects.

Primary Responsibilities

• Lead Generative AI projects in a cross-functional team environment.

• Apply advanced machine learning principles and algorithms, particularly for LLMs such as GPT-4, BERT, and Transformers.

• Utilize deep learning frameworks like TensorFlow, PyTorch, and Keras for model training.

• Maximize GPU utilization and efficiency through deep knowledge of computer architecture.

• Manage and optimize cloud-based resources (AWS, Azure, GCP) for deep learning model training.

• Implement containerization and orchestration using Docker and Kubernetes.

• Apply parallel and distributed computing principles for scalable model training.

• Integrate big data technologies like Hadoop and Spark into ML workflows.

• Adopt MLOps practices and tools to manage the end-to-end ML lifecycle.

Secondary Responsibilities

• Manage infrastructure for multiple ML projects, especially those involving deep learning models.