About the job
We are seeking ML research scientists and engineers with a strong background in machine learning, algorithms, decision making, and reinforcement learning to drive breakthrough innovations in intelligent systems. This position requires a hands-on approach to pioneer new technologies and bring them to life in entirely new product categories and form factors. If you thrive at the intersection of science, engineering, and product impact, this is your chance to make a visible mark at scale. You will work alongside world-class researchers and engineers, contributing to technologies that power the Apple ecosystem and publishing in top-tier scientific venues. You will work across disciplines—from hardware to human interaction—tackling the riskiest problems and transforming bold ideas into reality.
Responsibilities
Develop, train, and optimize adaptive ML algorithms that anticipate user needs and adapt to behavior in multi-tenant, conversational only environments.
Collaborate with cross-functional partners (hardware, UX, human interaction, physical systems) to invent and prototype features for entirely new form factors, with a variety of sensors, and user experiences.
Integrate ML models into multi-sensor, multi-modality product stack.
Design tools, analytics, and processes to perform deep, hands-on analysis and answer challenging technical questions.
Drive innovation from incubation to deployment, ensuring ideas make the leap from research into Apple products.
Iterate quickly based on feedback, technical constraints, and functional requirements.
Qualifications
Minimum
Master's, or PhD in Computer Science, Electrical Engineering, Statistics, or a related field.
Solid knowledge of Machine Learning methods and algorithms, statistical analysis, reinforcement learning, and computer science algorithms.
Strong programming skills in C++, Python.
Solid knowledge in deep learning frameworks such as PyTorch and TensorFlow.
Strong software engineering skills, delivering clean and well-tested code.
Strong problem-solving skills and ability to iterate quickly based on user feedback and technical constraints.
Excellent communication and collaboration skills, with ability to work independently or in small teams.
Preferred
Ph.D. in Computer Science or related field.
Recognized expertise in machine learning, automated planning, and decision theory.
Experience in out of distribution detection and diagnosis, automated planning and uncertainty estimation.
Proven experience with Generative AI and Large Language Models (prompt engineering, fine-tuning, etc.).
Prior experience building consumer-facing products is highly valued.