AIML - Sr Engineering Program Manager, ML Compute

Key Skills

AWS, Azure, CUDA/GPU programming, Machine learning techniques, MxNet, Natural Language Processing (NLP), Neural Networks, PyTorch, TensorFlow

Job Description

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you love taking on challenges that build a positive impact? Are you passionate about empowering many ground-breaking intelligent experiences to be made?

The AI/ML team at Apple is building groundbreaking technology... and we are looking for people like you! The Machine Learning Platform & Technology (MLPT) team in the AIML organization is seeking a senior technical product manager for its ML Training platform. This platform provides services to all internal Apple developers focused on providing efficient and scalable compute and processing for machine learning lifecycle from model experimentation to deployment for the features across the entire Apple consumer ecosystem.

We’re looking for someone with a record of building large-scale infrastructure for cloud platforms and a solid understanding of ML workflow. You will partner with the engineering teams and other product managers across the org to drive and influence our compute roadmap for improving engineering efficiencies, reducing cost, and ensuring resiliency for these services to enable scalability for Apple's ML use cases. You will also have the opportunity to be the leader with vision, identifying new technologies for adoption and be the central PM voice for interactions with public cloud providers, such as AWS and GCP, as well as internal Apple Cloud.

Key Qualifications

• 5+ years of Product and/or technical program management experience covering as many of the following areas as possible: distributed computing, large scale cloud infrastructure, GPU/TPU usage for ML training, software and computing architectures, container stack, and networking
• In-depth knowledge of computer systems and cloud infrastructure architecture
• Strong desire to learn with ability to problem solve and make sophisticated trade-offs
• In-depth software development and some data science experience
• Familiarity with AI frameworks (e.g. Tensorflow, Pytorch or MxNet) and/or GPU development experience
• Excellent interpersonal skills including ability to explain sophisticated technical topics to non-experts
• Experience in developing or deploying large scale GPU based AI applications, like Natural Language Processing and Recommendation, for training and inference or direct experience in building or managing cloud computing infrastructure and technologies
• Experience driving technical partnerships with internal and external cloud, silicon, software partners
• Proficiency in multitasking and leading sophisticated programs with a track record in developing and bringing outstanding platforms to market
• Self-motivated, independent, and proactive; demonstrated creative and critical thinking capabilities; can quickly (realtime) triage, prioritize, and lead multi-functional teams under pressure
• Outstanding interpersonal skills, including the ability to persuade and influence a diverse set of internal Apple and external public cloud partners
• Highly developed drive to improve how things work, with a proven track record of driving dramatic improvements for team quality, performance, agility, or effectiveness

Description

As a key EPM on the AIML team, you will be responsible for establishing partnerships with ML partners, understanding their use cases and improving the ease of use of the compute services.

You will collaborate with Apple’s AIML engineering teams to define a partnership strategy across the entire ML ecosystem including 3rd party public cloud, Apple’s internal cloud, silicon vendors, and OSS providers

We work with best in class engineering teams and developers across Apple to design the most efficient technologies to accelerate the ML lifecycle. You will be the trusted advisor to our customers to deeply understand their needs and help deliver low cost, high performance solutions that meet their use cases and business outcomes

Translate the product requirements to technical use cases, helping to see around corners, enabling risk mitigation for engineering execution through creating partnership roadmap for delivery

Define new computing modalities using resources native to the cloud and take that vision to market in collaboration with internal and external partners