Summary
Join us in enabling the next generation of intelligent experiences in Apple's products and services with the latest advancements in Generative AI and Large Language Models!

We are looking for a very experienced, machine learning engineer, who has also worked in ML infrastructure. Ideally, you should have experience with shipping intelligent features, end-to-end, and from idea to production. You should also have experience in building ML infrastructure to enable others to iterate faster and expertise in certain ML domains (preferably in Gen AI and LLM). You will help find novel solutions for our ML problems and collaborate with all ML teams at Apple to optimize our platform.

Are you ready to impact billions of our users?

Key Qualifications
A minimum of 3 years as tech lead
8 years of proven experience in machine learning related software engineering, such as: product, infrastructure, frameworks or tools
Strong expertise in machine learning domains, such as: CV, NLP, recommender systems, Gen AI or LLMs (preferred)
Proficient in ML training and deployment frameworks, like: Tensorflow, PyTorch, Faster Transformer, TensorRT, vLLM
Proficient in cloud computing and data processing infrastructure and tools: Kubernetes, Ray, PySpark, SQL
Ability to clearly and concisely communicate technical and architectural problems, while working with partners to iteratively find solutions

Description
You'll be part of Apple's internal Machine Learning Platform group that enables ML teams to iterate their projects faster, from: data engineering, labeling, training, online and offline evaluation, experimentation and more.

Bring your expertise to help us define and build the next set of features (given the new challenges in the latest advancement of generative AI and large language models). You will also partner closely with our customer and other internal partner ML teams cross the company to help further adopt and apply our platform, gain feedback and iterate our products (services, SDK and web UI) to be more user friendly and scalable.

Education & Experience
Bachelors in Computer Science, related field or equivalent experience

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