AIML - Staff Machine Learning Infrastructure Enginer, ML Platform & Technology
Job Description
Summary
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something!
As a Staff Engineer on ML Compute Team, you’ll join a phenomenal team of hardworking engineers and will be entrusted with a range of responsibilities. Your work will include: Collaborating with teams across Apple on ML workloads such as training, inferencing, fine tuning etc.; Driving the design and delivery of critical features to facilitate ML compute workloads; Effectively communicating complex features and systems in detail; Understanding industry & company- wide trends to help assess & develop new technologies. Your work will impact hundreds of millions of users and be essential to the success of some of the most visible current and future Apple features.
As a Staff Engineer on ML Compute Team, you’ll join a phenomenal team of hardworking engineers and will be entrusted with a range of responsibilities. Your work will include: Collaborating with teams across Apple on ML workloads such as training, inferencing, fine tuning etc.; Driving the design and delivery of critical features to facilitate ML compute workloads; Effectively communicating complex features and systems in detail; Understanding industry & company- wide trends to help assess & develop new technologies. Your work will impact hundreds of millions of users and be essential to the success of some of the most visible current and future Apple features.
Description
We are the team who build and maintain compute infrastructure to run ML workloads at Apple that include training, inferencing, fine tuning etc.. We are looking for an experienced software engineer who is excited by the opportunity to solve unique, large scale, highly complex technical problems to make ML workloads more stable, more reliable, more efficient and more cost effective. You will collaborate with a wide range of internal teams, listening intently to understand their challenges and true underlying needs. We are looking for candidates who share a passion for tackling complexity and building platforms that can scale through multiple orders of magnitude.
Key responsibilities:
- Scope, architect, and deliver innovative high-quality solutions
- Effectively communicate complex features and systems in detail
- Collaborate with teams across Apple on ML workloads such training, inferencing, fine tuning etc.
- Understand industry & company-wide trends to help assess & develop new technologies
- Code using Go, Python
- Conduct code reviews
- Help onboard new team members, provide mentorship and enable successful ramp up on your team's code bases
Key responsibilities:
- Scope, architect, and deliver innovative high-quality solutions
- Effectively communicate complex features and systems in detail
- Collaborate with teams across Apple on ML workloads such training, inferencing, fine tuning etc.
- Understand industry & company-wide trends to help assess & develop new technologies
- Code using Go, Python
- Conduct code reviews
- Help onboard new team members, provide mentorship and enable successful ramp up on your team's code bases
Minimum Qualifications
- Bachelors in Computer Science, engineering, or a related field
- 7+ years of hands-on experience in building scalable backend systems for training and evaluation of machine learning/deep learning models
- Proficient in relevant programming languages, like Python or Go
- Strong expertise in distributed systems, reliability and scalability, containerization, and cloud platforms
- Proficient in cloud computing and data processing infrastructure and tools: Kubernetes, Ray, PySpark
- Ability to clearly and concisely communicate technical and architectural problems, while working with partners to iteratively find solutions
Preferred Qualifications
- Advance degrees in Computer Science, engineering, or a related field
- Proficient in working with and debugging accelerators, like: GPU, TPU, AWS Trainium
- Proficient in ML training and deployment frameworks, like: JAX, Tensorflow, PyTorch, TensorRT, vLLM
Pay & Benefits
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