Our AI research team builds state-of-the-art cognitive systems that influence world-changing products. We pursue research into predictive reasoning with the goals of producing interpretable, interactive, self-supervising, and symbolic systems. As a researcher you drive the research agenda while seeking direct and indirect applied impact through delivering innovation, choosing impactful methods of research, engaging with academia, and publishing externally. Our focus is on reasoning, knowledge, and planning rather than on speech and natural language.
Now imagine what could you do here.
Hunger to discover and exploit new ML techniques.
Passion to build the next generation of decision-making, interactive systems.
In-depth knowledge of ML fundamentals.
Expertise and passion for a subfield of AI/ML that you believe will enable the teams main goal of improving interactive cognitive systems.
Great communication skills that can bring together diverse ideas.
Coding skills to support research and a belief that good code enables research. (Python, C++, PyTorch, or Tensor Flow)
Ability to plan and execute on a research agenda and the desire to work in a collaborative environment.
Preference for large scale data analysis and distributed computing for ML.
Based in Cambridge, you'll work closely with people across Apple worldwide. You will join an extraordinary team, including world-class software engineers, renowned academics, and expert machine learning practitioners who are all passionate about applying groundbreaking techniques to conversational AI.
You will identify, align, and communicate research toward state-of-the-art cognitive systems with the goal of preparing technical reports for publication and conference talks. Using your self-motivation, problem solving, and mental agility, you will collaborate with teams across Apple to develop and transfer ground-breaking AI/ML solutions. You will be responsible for delivering ML technologies aligned with the core values of Apple, ensuring the highest standards of quality, scientific rigor, innovation, and respect for user privacy.
To be successful we look for expertise in one of more of these areas: time-series learning, symbolic reasoning, self-supervision, hierarchical learning, interpretable ML, concept and transfer learning, graphical and structured models, on-line learning, and sequential decision making.
Is this you? Then we'd love to hear from you.
PhD or Masters degree in Machine Learning, Robotics, Computer Science, or equivalent science and engineering fields.
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