Machine Learning Systems Engineer

AppleCupertino, CA
68d

About The Position

The Siri organization is looking for passionate Machine Learning Systems Engineers to join us in developing and shipping state-of-the-art generative AI technology to advance Siri and Apple Intelligence for Apple's customers. Siri is being elevated by the huge opportunities that AI brings. The organization is responsible for training on-device & cloud models, evaluating various approaches, pushing the envelope with the latest generative AI research developments, and ultimately delivering product critical models that power Siri and Apple Intelligence experiences. These models ship across a wide range of products at Apple, including iPhone, Mac, Apple Watch and more, enabling millions of people around the world to get things done every day. Our team provides an opportunity to be part of an incredible research and engineering organization at Apple. By joining the team, you will work with highly talented machine learning researchers and engineers, and work on meaningful, challenging and novel problems.

Requirements

  • Not afraid of CUDA OOM or NCCL errors.
  • Ability to dig deep into an ML library to understand how tiny details impact the model.
  • Understanding of complex ML systems that include data, training pipeline, export, and inference engine.
  • Collaborative with experience working in large inter-teams projects.
  • Expertise in ML and LLM optimization such as quantization, KV Cache, Speculative Decoding.
  • Familiarity with ML training methodologies such as FSDP, DDP, and other parallelism.
  • Experience in an LLM training/eval library such as HuggingFace transformers, lm evaluation harness, Megatron-LM.
  • Experience in optimizing LLM models and deploying LLM models.
  • Proficiency in a compiled programming language (e.g. Swift, C/C++, Java).

Responsibilities

  • Work closely with Siri modeling teams and other cross-functional teams to optimize model training and inference.
  • Find opportunities to make models performant, train quicker, and run faster on Apple's custom Apple Silicon.
  • Write production-level code to train and deploy models that will impact Apple's customers and enrich their lives.
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