Apple made waves at WWDC 2024 by launching Apple Intelligence (beta coming in the fall), its answer to the booming generative AI space. But while this marks Apple’s public entry into the arena, the company has been quietly assembling an “AI army” behind the scenes for years, and continues to do so with more than 100 open positions related to data and AI/ML.

Prioritizing data privacy as it has done, Apple is emphasizing on-device processing with a new system called Private Cloud Compute. It is also giving Siri, which debuted roughly 14 years ago, a refresh. Through a partnership with OpenAI, Apple Intelligence will integrate OpenAI’s genAI tech access into various experiences, including Siri.

To truly grasp Apple’s AI ambitions, we need to peek behind the curtain at the team overseeing the AI strategy, starting with John Giannandrea, Apple’s senior vice president of machine learning and AI strategy who joined Apple in 2018. Since poaching Giannandrea from Google, Apple has steadily built up its bench of AI/ML talent under his guidance. This includes dozens of ML research scientists, engineers, product managers, and data experts focused on everything from core ML infrastructure to intelligent sensing and perception.

Want proof of Apple’s AI commitment? Look no further than their recent job postings. The company is dangling some hefty salaries—many exceeding $300,000—to attract the world’s best AI talent. Here’s a glimpse at the positions (open as of June 10) that reveal where Apple’s AI focus truly lies:

Job Title	Location	Salary Range
Lead Machine Learning Engineer, Frontier AI Technologies	Cupertino, CA	$199,800 – $364,100
AIML – Senior Software Engineer, Privacy – Machine Learning Platform and Technology	Cupertino, CA	$199,800 – $364,100
AIML – Senior Applied Research Lead, Health AI	Seattle, WA	$189,800 – $346,300
AIML – Sr Manager, Program Office, Data Operations	Cupertino, CA	$168,900 – $336,200
Software Engineering Manager – Intelligence Platform	Seattle, WA	$174,000 – $301,000
Visual Generative Modeling Research Engineer	Cupertino, CA	$170,700 – $300,200
Senior Privacy Engineer – Generative AI & Privacy Technologies	Cupertino, CA	$170,700 – $300,200
Apple Silicon GPU Driver Engineer – Prototyping	Cupertino, CA	$170,700 – $300,200
AIML Sr Software Development Engineer in Test	Cupertino, CA	$170,700 – $300,200
AIML Sr iOS/macOS Engineer, Siri and Information Intelligence	Cupertino, CA	$170,700 – $300,200
AIML – Software Engineer, Machine Learning Platform and Technologies	Cupertino, CA	$170,700 – $300,200
AIML – Senior Machine Learning Research Scientist, Biosignals Intelligence Group	Cupertino, CA	$170,700 – $300,200
AIML – Principal Staff Software Engineer, Privacy – Machine Learning Platform and Technology	Cupertino, CA	$170,700 – $300,200
AIML – Machine Learning SW/HW Co-Design Engineer, Machine Learning Platform & Infrastructure	Cupertino, CA	$170,700 – $300,200
AIML – Full Stack ML Engineer, LLM Optimization	Cupertino, CA	$170,700 – $300,200
AI Architect – Large Language Models & Generative AI	Cupertino, CA	$199,800 – $300,200

What the AI titles say about Apple’s strategy

These high-paying roles offer a glimpse into Apple’s specific priorities and how the company aims to differentiate itself in a competitive marketplace where rivals such as Google, Microsoft, and Meta routinely investing billions of dollars to stay at the forefront of the AI space.

Unsurprisingly, given Apple’s long-standing commitment to user privacy, several roles directly address this in the context of AI. The “Senior Privacy Engineer – Generative AI & Privacy Technologies” position, for example, highlights its focus on building privacy-preserving AI technologies from the ground up.

The box plot below shows the average salaries for select employees at Microsoft, Apple, OpenAI, and NVIDIA. The sample size included more than 1,400 open positions in all with many of the top-paid ones related to AI.

The review of open job postings from several Big Tech companies noted competitive pay from Apple for AI positions. The dataset includes positions across specializations, including titles such as the following:

• NVIDIA: Senior Deep Learning Systems Software Engineer, Senior Software Manager – Aerial, Senior Developer Relations Manager
• OpenAI: Engineering Manager, Fine-Tuning API, Research Engineer, AI Security & Privacy, Software Engineer, Data Acquisition
• Apple: Lead Machine Learning Engineer, Frontier AI Technologies, Senior Privacy Engineer – Generative AI & Privacy Technologies, AIML – Senior Applied Research Lead, Health AI
• Microsoft: Principal Software Engineering Manager, Senior Technical Program Manager, Senior AI Engineer

The diversity of Apple roles—from research scientists to software engineers—highlights the wide net the company is casting in its AI endeavors. Those jobs range from strengthening core infrastructure (“Machine Learning Platform and Technologies”) to pushing the boundaries of research (“Visual Generative Modeling,” “Biosignals Intelligence Group”).

Roles like “Lead Machine Learning Engineer, Frontier AI Technologies” suggests that Apple isn’t content with simply catching up—it’s aiming to be at the forefront. 

Details on Apple Intelligence

To power Apple Intelligence, the company has developed highly capable and efficient foundation models, including a ~3B parameter on-device model and a larger server model. These models were optimized extensively for performance, memory, and power efficiency on Apple hardware. Adapters, small neural network modules, allow the foundation models to dynamically specialize for specific tasks while keeping the base model weights frozen.

On its website, Apple has also emphasized its commitment to Responsible AI principles, ensuring that users’ private data is never used to train the models. The company follows principles to empower users, represent users authentically, design with care, and protect privacy. Apple’s Private Cloud Compute system prioritizes on-device processing to maintain data privacy.

In human evaluations, Apple’s models were generally preferred over open-source and commercial models of comparable size in terms of capabilities, safety, and instruction-following. The models also achieved lower violation rates on adversarial safety prompts compared to other models.

In its news announcement and hiring strategy, Apple is signaling its ambition to be more than just a player in the AI marketplace. Time will tell if it can stand out in a quickly moving marketplace.