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AIML - Machine Learning Engineer, Foundation Models at Apple
Cupertino, California, United States -
Full Time

Start Date

Immediate

Expiry Date

11 Mar, 26

Salary

0.0

Posted On

11 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Deep Learning, Natural Language Processing, Multi-modal Understanding, Python, JAX, PyTorch, Tensorflow, Distributed Systems, Large Models, Collaboration, Information Retrieval, On-device Intelligence, Privacy Protections

Industry

Computers and Electronics Manufacturing

Description
We are a group of engineers and researchers responsible for building foundation models at Apple. We build infrastructure, datasets, and models with fundamental general capabilities such as understanding and generation of text, images, speech, videos, and other modalities and apply these models to Apple products. We are looking for engineers who are passionate about building systems that push the frontier of deep learning in terms of scaling, efficiency, and flexibility and delight millions of users in Apple products. DESCRIPTION We believe that the most interesting problems in deep learning research arise when we try to apply learning to real-world use cases, and this is also where the most important breakthroughs come from. You will work with a close-knit and fast growing team of world-class engineers and scientists to tackle some of the most challenging problems in foundation models and deep learning, including natural language processing, multi-modal understanding, and combining learning with knowledge. MINIMUM QUALIFICATIONS Proven track record in training or deployment of large models or building large-scale distributed systems. Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow. Ability to work in a collaborative environment. PhD, or equivalent practical experience, in Computer Science, or related technical field. PREFERRED QUALIFICATIONS Web-scale information retrieval Human-like conversation agent Multi-modal perception for existing products and future hardware platforms On-device intelligence and learning with strong privacy protections
Responsibilities
You will work with a team of engineers and scientists to tackle challenging problems in foundation models and deep learning. The focus will be on applying learning to real-world use cases.