AIML - Machine Learning Engineer, Foundation Models

What you'll do

• Design and implement scalable, high-performance machine learning infrastructure for multi-modal foundation models.
• Optimize models for performance, efficiency, and on-device intelligence specifically for Apple silicon.
• Develop mid-training approaches to bridge general capabilities with task-specific performance.
• Implement machine learning systems that adhere to stringent privacy and security requirements.
• Solve frontier problems in reward modeling to resist reward hacking and handle sparse rewards.
• Align models for diverse tasks ranging from creative outputs to precise, action-taking workflows.
• Transform research prototypes into production-ready AI solutions across the full training lifecycle.
• Manage a small team of engineers as required.

What we're looking for

• MS or PhD in Computer Science, Machine Learning, or a related technical field.
• Expert-level programming skills in Python.
• Proficiency in machine learning frameworks such as Jax, PyTorch, or TensorFlow.
• Strong background in distributed training, model optimization, and machine learning infrastructure.
• Experience with large-scale model training and deployment.
• Familiarity with Kubernetes, Docker, and cloud platforms like AWS, GCP, or Azure.
• Experience with foundation models, large language models, or multi-modal AI systems (preferred).
• Published research or significant contributions to open-source ML projects (preferred).