Machine Learning Infrastructure Manager

Sunnyvale, California, United States
Machine Learning and AI

Summary

Posted:
Role Number:200545800
Looking to make a difference in Apple's product experiences? Consider joining the Video Computer Vision (VCV) organization, where we excel in real-time video analysis and cutting-edge reasoning algorithms. Responsible for groundbreaking innovations like FaceID and vision pro Input (including hand and gaze tracking). VCV is now seeking exceptional leaders to spearhead our ML Infrastructure & System team. Collaborating closely with our researchers, you'll help shape the next generation of AI capabilities.

Key Qualifications

  • Collaborate cross-functionally: Partner with AI researchers and infrastructure teams at Apple to shape our roadmap and execute strategic and tactical operations.
  • Lead with vision: Develop forward-looking tools and platforms for handling multi-model large language models.
  • Manage teams effectively: Recruit top talent, offer technical leadership, set clear expectations, and foster a positive work environment.
  • Ensure product efficiency: Participate in product design reviews to guarantee the efficient and secure use of ML infrastructure.
  • Establish engineering excellence: Provide guidance and establish processes for engineering excellence and operational sustainability.

Description

8+ years of software development experience. 3+ years leading ML infrastructure engineering teams. Experience with large-scale data domains, including data ingestion, processing, ETL, management, governance, compliance, and tools. Familiarity with commercial and/or open-source storage frameworks and compute platforms such as Apache Spark, Apache Flink, and Ray. Knowledge of analytics databases like Snowflake, Redshift, and BigQuery. Proficiency in data pipeline and workflow management tools. Familiarity with ML principles and experience with frameworks like TensorFlow and PyTorch. Understanding of model hosting and sharing platforms such as Hugging Face, Weights & Biases, and model zoos. Strong organizational skills and experience working on large multi-functional teams. Track record of driving product innovations and opportunities across diverse collaborators. Passion for developing best practices and defining effective strategies. Commitment to operational excellence through automation and engineering processes. Solid background in distributed systems and engineering. Exceptional problem-solving skills and ability to thrive in a fast-paced and dynamic environment.

Education & Experience

BS and a minimum of 10 years relevant industry experience

Additional Requirements

Pay & Benefits