Senior Machine Learning Engineer, Services/MLOps

What you'll do

• - Build and optimize infrastructures for large foundation model training on thousands of GPUs.
• - Profile GPU utilization to craft strategies for optimizing ML model latency in inference and training.
• - Architect and optimize end-to-end ML pipelines for scalability, efficiency, and robustness.
• - Recommend appropriate models, evaluation metrics, and governance approaches based on data analysis.
• - Engage throughout the product lifecycle for architecture, design, deployment, and optimization of ML systems.

What we're looking for

• 5+ years of ML engineering experience, specializing in generative AI like LLMs.
• Deep expertise in building large-scale foundation model infrastructures for training on thousands of GPUs.
• Strong Python and deep learning skills with extensive experience using PyTorch or TensorFlow.
• Familiarity with distillation, transformers, diffusion models, and generative image/video technologies.
• Knowledge of deployment technologies such as Docker, ML Ops, and cloud platforms like Azure/AWS.
• Excellent problem-solving abilities and a data-driven approach to complex issues.
• Strong verbal and written communication skills for cross-functional team collaboration.