Machine Learning Algorithm Engineer - Auto Focus

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $147,400–$272,100 / yr
Posted: 56 days ago
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $221k

This role $210k

$132k most similar roles pay here $287k

This role pays more than 50% of similar roles. Most pay $194,500–$246,875 — the shaded band above. At the midpoint, this role pays about $210k versus about $221k for comparable roles.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Machine Learning Algorithm Engineer - Auto Focus

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Join Apple's Camera Algorithm team as a senior Machine Learning Engineer and drive the development of advanced machine learning-based auto-focus technologies for real-time capture across all camera products. You will lead the end-to-end architecture and productization of novel AF algorithms, working independently to define long-term ML roadmaps and integrate cutting-edge systems on Apple’s camera platforms. Your responsibilities include collaborating with SOC design, hardware, and firmware teams to optimize system-level flows and influence future silicon designs for enhanced auto-focus features. Ideal candidates possess a master's degree in a relevant field, expertise in PyTorch or TensorFlow, and hands-on experience with low-level vision tasks such as dataset curation and data augmentation. Strong knowledge of optics and image quality metrics is preferred, along with a track record of innovation in top-tier computer vision publications and patents.

Skills

PyTorch TensorFlow Python C Apple Neural Engine Image Signal Processor TrueDepth Camera LiDAR Scanner CVPR ICCV ECCV Modulation Transfer Function Spatial Frequency Response Acutance Blur Estimation Stereo Disparity Depth Estimation Optical Flow Estimation Sensor Fusion Dataset Curation Data Augmentation

What you'll do

Design and implement advanced machine learning-based auto-focus algorithms for Apple's camera products.
Lead the end-to-end architecture and productization of novel ML systems for seamless auto-focus experiences.
Collaborate with SOC architecture teams to influence future silicon designs impacting auto-focus performance.
Develop sophisticated training datasets and tooling for machine learning based auto-focus development.
Partner with hardware and firmware teams to optimize system-level flows for ML algorithms in camera products.

What we're looking for

MS in Computer Science, Machine Learning, Electrical Engineering, or related field.
Experience defining datasets for machine learning network training on low-level vision tasks.
Expertise in modern ML frameworks like PyTorch or TensorFlow/TFLite/LiteRT.
Strong software engineering skills with proficiency in Python and C.
Practical experience in machine learning for computer vision applications such as auto-focus.
Knowledge of optics principles and image quality metrics impacting sharpness evaluation.

Hybrid

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Machine Learning Engineer

Austin, TX 50 days ago

Python TensorFlow PyTorch scikit-learn R Java cloud platforms scalable computing resources machine learning pipelines data analysis statistics optimization probability theory experimental methodologies CI/CD

Hybrid

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