Machine Learning Algorithm Engineer

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $150,400–$225,300 / yr
Posted: 2 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $218k

This role $188k

$137k most similar roles pay here $279k

This role pays less than 73% of similar roles. Most pay $187,850–$248,750 — the shaded band above. At the midpoint, this role pays about $188k versus about $218k for comparable roles.

Based on 240 similar postings.

Employer

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 2240 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1831 roles with salary data.

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At a glance

TL;DR · Machine Learning Algorithm Engineer

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Machine Learning Algorithm Engineer - Auto Focus will serve as a technical leader responsible for the end-to-end architecture, prototyping, and productization of advanced machine learning-based auto-focus algorithms. This role involves defining the long-term roadmap for autofocus systems integrated on camera platforms to ensure seamless performance in various lighting conditions. The engineer will collaborate with silicon, hardware, and firmware teams to develop multi-modal hybrid algorithms utilizing the Apple Neural Engine, Image Signal Processor pipelines, TrueDepth Camera, and LiDAR Scanner. Key responsibilities include creating training tools, managing data curation for low-level vision tasks, and designing systems for real-time capture solutions. Required skills include proficiency in Python and C, expertise in PyTorch or TensorFlow/TFLite/LiteRT, and knowledge of optics and image quality metrics like Modulation Transfer Function and Point Spread Functions to solve complex camera focus problems.

Skills

Machine Learning Computer Vision Python C PyTorch TensorFlow TFLite LiteRT Image Signal Processor Silicon Design Data Augmentation Sensor Fusion

What you'll do

Own the end-to-end architecture, prototyping, and productization of machine learning-based auto-focus algorithms.
Define the long-term technical roadmap for multi-modal hybrid auto-focus systems.
Design novel learning-based systems integrated with Apple's hardware platforms to improve performance in various lighting conditions.
Coordinate sub-teams to develop training pipelines and tools for machine learning based auto-focus development.
Collaborate with SOC, hardware, and firmware teams to influence silicon design and optimize system-level flows.
Develop solutions utilizing the Apple Neural Engine (ANE), Image Signal Processor (ISP) pipelines, and LiDAR sensors.
Create high-quality datasets and curation strategies for training machine learning networks on low-level vision tasks.

What we're looking for

MS in Computer Science, Machine Learning, Electrical Engineering, or a related field.
Experience defining datasets for machine learning network training on low-level vision tasks and data augmentation strategies.
Expertise in modern machine learning frameworks such as PyTorch or TensorFlow/TFLite/LiteRT.
Strong software engineering and architectural skills with proficiency in Python and C.
Experience with machine learning for practical low-level computer vision applications like auto-focus, depth estimation, or optical flow (preferred).
Experience defining datasets for training temporal networks (preferred).
Knowledge of optics and image quality metrics such as PSF, DOF, MTF, and blur estimation (preferred).
Track record of innovation through publications in top-tier computer vision conferences or patents (preferred).