AIML - Staff ML Infrastructure Engineer, ML Platform & Technology - ML Compute

Key Skills

Aartificial intelligence, AWS, Design, GPUs, Infrastructure as code, JAX framework, Machine learning techniques, MLOps tools, PyTorch, TensorFlow

Job Description

As a staff engineer on ML Compute team, your work will include:

• Drive large-scale training initiatives to support our most complex models.
• Operationalize large-scale ML workloads on Kubernetes.
• Enhance distributed cloud training techniques for foundation models.
• Design and integrate end-to-end lifecycles for distributed ML systems
• Develop tools and services to optimize ML systems beyond model selection.
• Architect a robust MLOps platform to support seamless ML operations.
• Collaborate with cross-functional engineers to solve large-scale ML training challenges.
• Research and implement new patterns and technologies to improve system performance, maintainability, and design.
• Lead complex technical projects, defining requirements and tracking progress with team members.
• Mentor engineers in areas of your expertise, fostering skill growth and knowledge sharing.
• Cultivate a team centered on collaboration, technical excellence, and innovation.

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 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

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.