IML - Staff Machine Learning Engineer, Ranking Quality - Siri & Information Intelligence - Apple, Inc. : Job Details

Want to build the machine learning platform that engineers rely on to develop next-generation Apple Intelligence products and services? As a machine learning engineer on our team, you will create platforms and tools to enable performant, scalable ML workloads for Apple's AI-driven experiences. Join our team of highly skilled, impact-focused engineers! This role also includes opportunities to open source your work and publish at top ML conferences.

Description

We're searching for strong machine learning engineers to help build the next-generation platform for training deep learning models at scale. You'll be part of a team of distributed systems and machine learning experts, focusing on the reliability, scalability, and performance of ML-related workloads including model training, inference, and data processing. We're looking for candidates with polished coding skills as well as a passion for distributed systems and machine learning. In exchange, we offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities—all at one of the best companies in the world. Design and develop components for our centralized, scalable ML platform. Push the limits of existing solutions for large-scale ML workloads. Develop novel techniques to circumvent the limitations of these solutions. Deploy your techniques on high-impact tasks from our partners across the company building new Apple Intelligence products and services. We encourage publishing novel work at top ML conferences and releasing contributions as open source.

Minimum Qualifications

• Strong programming skills in Python or Go
• Understanding of data structures, software design principles, and algorithms
• Experience building large-scale distributed systems with tools such as Kubernetes, Kafka, Prometheus, etc.
• Experience with deep learning frameworks, such as PyTorch or JAX
• Minimum of 7+ years of industry experience
• Bachelor's in the area of Computer Science or equivalent, or a related domain

Preferred Qualifications

• Experience building large-scale deep learning infrastructure or platforms for distributed model training
• Experience with large-scale AI training infrastructure components, such as accelerators, network fabrics, CUDA, NCCL, RDMA
• Experience working with public cloud vendors such as AWS, GCP, Azure
• Experience developing model parallel and data parallel training solutions and other training optimizations
• Familiarity with recent developments in foundation model architectures for language and multimodal
• Publication record at ML conferences such as MLSys, NeurIPS, etc.
• Masters or PhD in the area of Computer Science or equivalent, or a related field

Compensation and 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 $166,600 and $296,300, 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 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.

Equal Opportunity Employer

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.