AIML - Machine Learning Engineer, Foundation Models

What you'll do

• Design and implement high-performance machine-learning infrastructure for foundation models across text, image, speech, and multimodal domains.
• Collaborate to productionize state-of-the-art AI algorithms and optimize models for performance, efficiency, and on-device intelligence.
• Implement systems with stringent privacy and security requirements; may manage a small team of engineers.

What they ask for

• MS or PhD in Computer Science, Machine Learning, or a related technical field.
• Expert-level programming skills in Python; proficiency in 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, cloud platforms (AWS, GCP, Azure), and distributed computing frameworks.

Nice to have

• Experience with foundation models or large language models, or a background in multimodal AI systems.
• Experience productionizing research prototypes, ML research or open-source contributions, or understanding of on-device machine-learning techniques.

Pay

$184,700 and $324,800 USD base salary

Tools

Python, Jax, PyTorch, TensorFlow, Kubernetes, Docker, AWS, GCP

AI focus

Develop and train foundation models, including pre-training and mid-training; tackle reward modeling and alignment for agentic workflows; optimize models for Apple silicon, on-device intelligence, and private experiences.