AIML - Staff Software Engineer, ML Compute - ML Platform & Technologies

About the position

As part of the ML Compute team, you will be at the heart of designing, building, and maintaining the compute infrastructure that enables model training, tuning, and other ML tasks for machine learning, artificial intelligence, and computer vision applications. Make an impact by shaping and owning critical compute components, and be proud to contribute to the infrastructure that enables intelligent experiences across all Apple products and services, used by billions of people worldwide.

Responsibilities

• Own the architecture, design, development, and operations of large-scale systems designed for machine learning.
• Develop custom scheduling, resource management solutions, and fleet management for our ML model training compute infrastructure.
• Collaborate with multi-functional teams, integrate with Kubernetes in on-premises and cloud provider clusters, and enable seamless integration with NVIDIA GPUs and other ML accelerators.
• Partner with data scientists and machine learning engineers across different Apple organizations to define high-impact product features and deliver them with quality.
• Lead a group of engineers to deliver high-quality products/services.
• Support junior engineers by providing advice, mentoring, and educational opportunities.

Requirements

• Bachelors in Computer Science
• 10+ years of industry related experience, working in collaborative environments
• Experience with public cloud infrastructure like: Kubernetes, Amazon EC2 and EKS, Google Cloud Platform
• Strong software development skills, with proficiency in relevant languages (ex. Golang, Python)
• Strong problem solving skills and ability to write performant and high-quality code
• Proficient understanding of the software development process, including unit testing and release management
• Excellent interpersonal skills; able to work independently as well as in a team; can take feedback and iterate on a solution in a collaborative setting

Nice-to-haves

• Strong understanding of batch scheduling systems and high-performance computing environments
• Experience using system monitoring tools, automated testing frameworks and CI/CD pipelines
• Experience with GPUs and/or other ML accelerators in the context of Machine Learning
• A passion for making simple, robust, and scalable platforms used by other engineering teams
• Flexibility/adaptability for working in a dynamic environment with different frameworks and requirements
• Masters or PhD in Computer Science

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses — including tuition
• Discretionary bonuses or commission payments
• Relocation assistance
• Participation in Apple's discretionary employee stock programs