Aiml - Site Lead & Lead Researcher, Foundation Models
Apple
United States Of America, United States
Not specified
Leadership experience in technical teams
Strong publication record in deep learning
Expert-level python programming skills
Apple is seeking a Site Lead & Lead Researcher for its Foundation Models team, responsible for overseeing a strategic hub focused on developing and optimizing foundation models for Apple's products. The role requires a combination of leadership, deep learning expertise, and the ability to foster collaboration across teams
Job Summary
The role involves leading a strategic hub responsible for building and advancing frontier foundation models optimized for Apple silicon.
Candidates must balance strategic oversight with hands-on research direction to tackle challenging problems in natural language processing and multi-modal understanding.
The position requires fostering a culture of research excellence while bridging the gap between deep learning research and product integration.
Matching Summary
Match Score: 85
Apple is seeking a Site Lead & Lead Researcher for its Foundation Models team, responsible for overseeing a strategic hub focused on developing and optimizing foundation models for Apple's products. The role requires a combination of leadership, deep learning expertise, and the ability to foster collaboration across teams.
Skills & Requirements
Must-have
Leadership experience in technical teams
Strong publication record in deep learning
Expert-level Python programming skills
Proficiency in JAX PyTorch or TensorFlow
PhD in Computer Science or equivalent
Nice-to-have
Experience with web-scale information retrieval
Track record building human-like conversation agents
Background in on-device intelligence and privacy
History of mentoring researchers to senior roles
Experience leading research through product commercialization
Key Requirements
Demonstrated success leading technical teams
PhD in Computer Science or related field
Expert-level skills in Python and deep learning toolkits
Proven track record of applying deep learning at scale