AIML - Engineering Manager, ML Infrastructure & Frameworks

    • Apple, Inc.
  • Cupertino, CA
  • Posted 13 days ago | Updated 7 hours ago

Overview

On Site
USD 183,400.00 - 316,900.00 per year
Full Time

Skills

Large Language Models (LLMs)
Software development
Open source
Data processing
Apache Spark
Apache Flink
Organizational skills
Operational excellence
Problem solving
Product design
Computer science
Deep learning
GPU computing
Machine Learning (ML)
Data
Analytics
Planning
Storage
Computer networking
Training
Leadership
GPU
PyTorch
Management
Automation
Roadmaps
Collaboration
Kubernetes
Strategy
Design
Artificial intelligence
Operations
Mentorship
Sustainability
TensorFlow
JAX
Streaming
Apache Kafka
Algorithms
Benchmarking
Modeling
Payments

Job Details

Summary

The Data Platform team within the AIML organization powers analytics, experimentation, and ML feature engineering to power Siri, Search, and other ML features we all love in our Apple ecosystem. The mission of the Data Platform org is to provide our engineers and data scientists with an innovative, reliable, secured, and easy-to-use infrastructure for ingesting, storing, processing, and interacting with data and ultimately help the teams that build data-intensive applications be successful. You will work with many cross-functional teams and own the planning, execution, and success of technical projects with the ultimate purpose of improving Siri and Search experience for Apple customers. We are looking for an Engineering Manager for the ML acceleration team that scales, manages and optimizes the infrastructure (Compute, Storage & Networking) for large scale ML training and inference. Come join us and be part of the Data Platform journey.

Key Qualifications

8+ years of software development experience3+ years leading ML infrastructure engineering teamsExperience with commercial and/or open-source large-scale data processing, ML training and inference, storage frameworks, and platforms such as Apache Spark, Apache Flink, Ray, etcExperience optimizing frameworks and infrastructure for large-scale ML training on GPU-accelerated hardwareExperience with frameworks such as Deepspeed, Horovod, Hugging Face Accelerate, PyTorch LighteningExperience in managing and optimizing ML platforms and infrastructureStrong organizational skills and experience working on large multi-functional teamsExperience in influencing and driving key product innovations and opportunities across diverse collaboratorsPassionate about operational excellence through proper automation and engineering processesStrong distributed systems and engineering backgroundSuperb problem-solving skills and ability to thrive in a fast-paced and dynamic environment.

Description

Join Apple's Data Platform team as an Engineering Manager to deliver the best experiences across Siri, Spotlight, and Safari. You will be responsible for defining and driving the roadmap for multi-GPU acceleration for ML training for our data platform, offering the best infrastructure across our stack at Apple scale. You will collaborate with cross-functional teams of innovative software engineers, product managers, and engineering managers to continually improve our efficiency and training performance. We embrace the use of open-source technologies, including Kubernetes and Spark, Flink, Trino, and Iceberg, for data processing. RESPONSIBILITIES INCLUDE:- Define and drive technical vision, roadmap, and strategy for our platform- Guide the design and development of new AI and ML acceleration frameworks and tools - Participate in product design reviews to ensure efficient and secure use of ML infrastructure- Collaborate with stakeholders and cross-functional leaders in engineering, product, and operations across Apple to ensure the correct adoption of our data and ML platform - Lead and mentor new hires or junior engineers - Provide guidance and establish processes to ensure engineering excellence, efficiency, and operational sustainability of our platform - Foster a healthy, inclusive, collaborative, and technology-driven culture

Education & Experience

B.S or M.S. Degree in Computer Science/Engineering, or equivalent work experience

Additional Requirements

  • Bonus if you have experience in the following areas:
  • - Working with or developing Large-language models (LLMs)
  • - Working with ML frameworks such as PyTorch, TensorFlow, Jax
  • - Working with streaming data processing frameworks such as Apache Flink, Kafka Streams, Spark Streaming
  • - Developing and optimizing algorithms that run efficiently on resource-constrained platforms
  • - Designing, implementing, and benchmarking/fine-tuning ML/deep learning algorithms
  • - Working with GPU computing or ML modeling frameworks.


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 $183,400.00 and $316,900.00, 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.

    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.