Research Scientist - LLM Efficiency

We're seeking research scientists and engineers to create breakthrough innovations in machine learning. We are particularly interested in efficiency of frontier models, including LLMs and diffusion models. You will work in an organization of world-class machine learning researchers and engineers. Our work powers cutting-edge technologies across the Apple ecosystem and is published in the most selective scientific journals and conferences. We are a team of best-in-the-world research scientists and engineers with deep experience in machine learning.

We work on exciting new technologies that bring joy to millions of people. In our daily work, the team stays innovative, productive, and fun by sharing several key values:

• Passion for the mission: We're here to make something extraordinary. We seek out whatever work is right and strive for the best possible results.
• Modesty: Finding the right answer is more important than being right. We search for solutions as a team and value clear-eyed feedback..
• Lean habits: You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions. Designing, training, and adapting frontier models to improve efficiency and performance. Designing and conducting empirical studies to better understand frontier models. Developing prototypes to demonstrate the effectiveness of the models and algorithms developed. Engaging with the academic community by publishing papers and presenting your work. Collaborating with product teams across Apple to ship research. Significant experience building complete prototypes that achieve state-of-the-art performance in your areas of expertise. A publication record at relevant conferences, such as NeurIPS, ICML, ICLR, and COLM. Comfort working across the entire ML research stack, from low-level systems programming to high-level algorithm development. Solid software engineering skills and experience working with complex systems. Fluency in Python. Expertise in ML algorithms and best practices for working with deep learning systems. Proficiency with ML modeling frameworks such as PyTorch and JAX. A bachelor's, master's, or PhD degree in Computer Science, Electrical Engineering, Mechanical Engineering, or a related field, or equivalent academic or professional experience.

The job is published on Apple’s website. Open the original posting ↗ to submit your application. Screeningpass does not fill in a form for you.

Start a contact search from this page. Screeningpass suggests up to three people connected to the role. Choose whom to write to, then Screeningpass looks for their professional email and prepares a message. You review it and send it yourself with Gmail. An email address is not always available, and a reply is never guaranteed.

A search costs 1 credit. Your credit is returned if the search fails. Signing up gives you 3 credits, enough for 3 searches.

Screeningpass brings together internships, apprenticeships and jobs published by companies. For a job, Screeningpass finds someone to contact at the company, looks for their professional email and prepares a message using your CV. See how it works in detail.