Machine Learning Algorithm Engineer - Auto Focus

Apple Inc.; Cupertino (CA); On-site; USD 150,000 - 225,000; Full time

Benefits offered by this job

Stock programs

RSU

ESPP

Medical & dental coverage

Retirement benefits

Discounted products

Free services

Tuition reimbursement

Job summary

Apple Inc. in Cupertino seeks a Machine Learning Algorithm Engineer - Auto Focus to own end-to-end architecture and rapid prototyping of ML-based auto-focus algorithms integrated into Apple camera platforms, delivering seamless focus in bright and low light.

You will lead cross-functional work with SOC, hardware, and firmware teams to deploy advanced learning-based AF features, mentor others, and drive the long-term ML roadmap for AF across Apple products.

Qualifications

• MS degree in CS/ML/EE or related field required.
• Experience defining datasets for ML training on vision tasks and data augmentation.
• Proficiency with modern ML frameworks (PyTorch, TensorFlow) and Python/C software engineering.

Responsibilities

• Lead end-to-end ML-based auto-focus development and architecture.
• Architect solutions leveraging ML, ANE, ISP pipelines, TrueDepth Camera, LiDAR, and other hardware.
• Mentor and collaborate with cross-functional teams to deploy real-time AF features.

Skills

Python

C

ML datasets

Software architecture

Education

MS in Computer Science / Machine Learning / Electrical Engineering

Tools

PyTorch

TensorFlow/TFLite/LiteRT

Job description

Machine Learning Algorithm Engineer - Auto Focus

Cupertino, California, United States Hardware

As a technical leader within the team, you will own the end-to-end architecture, rapid prototyping, and productization of advanced machine learning-based auto-focus algorithms. You will maneuver through ambiguity independently to drive the long-term ML roadmap for AF, spearheading the design of novel learning-based systems integrated on Apple camera platforms which achieve seamless auto-focus user experience in any scene condition in both bright and low light. You will determine methods and procedures on complex projects, frequently acting as the representative for your area while leading cross-functional work to deploy enhanced machine learning based AF features. This includes coordinating the activities of sub-teams to create sophisticated architecture, training and tooling for machine learning based auto-focus development.

Description

You will partner deeply with the SOC architecture team to influence future silicon designs, the hardware team to evaluate new camera components impacting auto-focus, and the firmware team to optimize system-level flows for machine learning algorithms. The ideal candidate is a visionary problem-solver who thinks originally, resolves highly complex issues in creative ways, and is a proven mentor capable of inspiring innovation among others.

Responsibilities

• You will provide meaningful and significant contributions to the company's objectives by helping set the technical direction for next-generation multi-modal hybrid auto-focus algorithms.
• You will architect solutions that leverage advanced machine learning, the Apple Neural Engine (ANE), Apple-designed Image Signal Processor (ISP) pipelines, TrueDepth Camera, LiDAR Scanner, and other specialized hardware to redefine how camera auto-focus works at a fundamental level.
• You will act as a key technical pillar, creating partnerships across Silicon Design, Camera Hardware/Software, and Quality Assurance towards the creation of novel solutions in the space of real-time, machine learning based auto-focus capture solutions applicable across all of Apple’s products.

Minimum Qualifications

• MS in Computer Science, Machine Learning, Electrical Engineering, or a related field.
• Experience in defining datasets for machine learning network training on low-level vision tasks as well as dataset curation and data augmentation strategies for robust training.
• Expertise in modern machine learning (ML) frameworks and libraries, specifically PyTorch or TensorFlow/TFLite/LiteRT.
• Strong software engineering and architectural skills, highly skilled at coding in Python and C.

Preferred Qualifications

• Experience with machine learning for practical low level computer vision applications including one or more of the following areas: auto-focus, stereo disparity/depth, depth estimation, defocus/blur estimation, optical flow estimation, sensor fusion.
• Experience with defining datasets for training temporal networks.
• Good knowledge of optics (Point Spread Functions, Depth-of-Field, etc.) and image quality metrics impacting critical image sharpness evaluation (Modulation Transfer Function, Spatial Frequency Response, Acutance, Blur/Defocus Estimation etc).
• Track record of pioneering innovation comprising publications in top-tier computer vision conferences (e.g., CVPR, ICCV, ECCV) and/or patents.

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 $150,400 and $225,300, 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 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.

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Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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

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Apple accepts applications to this posting on an ongoing basis.