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Job Description

Apple is seeking a Machine Learning Engineer in Sunnyvale, California, to develop ML models for computer vision and graphics within Face and Body/vision technologies. You will drive the end-to-end ML lifecycle to ship features on iOS and VisionOS, collaborating with ML, data, and software engineers across teams.

Location

Sunnyvale, CA (onsite)

Responsibilities

  • Design data collection strategies and process data as part of the ML cycle.
  • Design models and run experiments within the ML lifecycle.
  • Validate and perform QA in real-world deployments.
  • Conduct applied research to adapt or implement state-of-the-art methods to ship features on iOS and VisionOS.
  • Collaborate with other ML engineers, data engineers, and software engineers across teams.

Requirements

  • 3+ years of experience developing ML projects for computer vision or graphics applications.
  • Proficiency in Python and software engineering fundamentals.
  • Experience with PyTorch.
  • BA/BS degree in computer vision, computer graphics, machine learning, or a related field.

Technologies

  • Python
  • PyTorch

Benefits

  • Comprehensive medical and dental coverage
  • Retirement benefits
  • A range of discounted products and free services
  • Reimbursement for educational expenses, including tuition
  • Apple discretionary employee stock programs
  • Eligible for discretionary restricted stock unit awards
  • Ability to purchase Apple stock at a discount via the Employee Stock Purchase Plan
  • Discretionary bonuses or commission payments
  • Relocation assistance

Compensation

Base pay range for this role is $150,400 to $277,600 per year. The final offer depends on skills, qualifications, experience, and location.

Preferred Qualifications

  • MS or PhD in computer vision, computer graphics, machine learning, computer science, computer engineering, or related fields.
  • Self-motivated with a proven ability to prioritize and deliver tasks on schedule.
  • Excellent communication and experience working with cross-functional teams.

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