AI Software Engineer, Apple Cloud AI Platform

$129K - $225K Cupertino, CA, US Mid Level AI Software Engineer

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Skills & Technologies

AwsAzureDockerGcpHugging FaceJavascriptLangchainPrompt EngineeringPythonPytorch

About This Role

AI job market dashboard showing open roles by category

Apple Cloud AI Platform powers the machine learning, AI, and data systems behind intelligent experiences across Apple's consumer products. We are looking for a Software Engineer who is eager to build the tools, interfaces, and workflows that ML developers and researchers use every day from intuitive front\-end experiences to backend services and ML integrations at Apple scale. This is a great opportunity for an early\-career engineer who wants to grow across the full stack from building intuitive UIs for internal platforms to integrating ML services and workflows into production systems working at Apple scale.

Description

In this role you will work alongside a team of senior engineers to build and ship features across our AI and Data platform. You will contribute to both internal front\-end products that teams use to interact with our platform as well as the backend services and ML integrations that power them. You will be expected to take ownership of features end to end, write clean and tested code, and collaborate closely with teammates, product managers, and partner teams. You will grow quickly by working on real systems at Apple scale, with mentorship and clear paths to increased ownership.","responsibilities":"Build and maintain product features for internal developer platforms and AI tooling using React and TypeScript

Integrate UI surfaces with backend APIs and ML services to create end\-to\-end, user\-facing workflows

Contribute to backend services supporting ML workloads, including data ingestion, model evaluation, and inference endpoints

Write well\-tested, production\-ready code with attention to reliability, performance, and developer experience

Collaborate with senior engineers, product managers, and partner teams to understand requirements and deliver solutions

Participate in design reviews, code reviews, and on\-call rotations as you grow into the role

Contribute to improving observability, monitoring dashboards, and tooling for ML systems

Document your work and contribute to team knowledge sharing

Preferred Qualifications

Experience building product experiences or web applications with React or a comparable modern framework

Experience with cloud environments (AWS, GCP, or Azure), Docker, or CI/CD pipelines

Familiarity with ML frameworks such as PyTorch, Hugging Face, or LangChain

Exposure to LLM application development, RAG, prompt engineering, evaluation pipelines, or agentic workflows

Experience with data infrastructure tools such as Spark, Kafka, or SQL\-based analytics systems

Ability to work independently on scoped features with minimal supervision

Minimum Qualifications

1 or more years of industry experience building production software

Proficiency in Python and JavaScript/TypeScript

Familiarity with REST APIs and backend service integration

Basic understanding of ML concepts, model inference, evaluation, or data pipelines

Contributions to open\-source projects or experience building internal developer tooling

Strong communication skills and ability to work collaboratively in a team environment

Curiosity, a growth mindset, and willingness to work across the stack

BS/MS in Computer Science, Software Engineering, or a related field with applicable internship or project experience

Pay \& Benefits

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 $129,300 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. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Salary Context

This $129K-$225K range is below the median for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).

Role Details

Company Apple
Title AI Software Engineer, Apple Cloud AI Platform
Location Cupertino, CA, US
Category AI Software Engineer
Experience Mid Level
Salary $129K - $225K
Remote No

About This Role

AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.

The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.

Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Apple, this role fits into their broader AI and engineering organization.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

What the Work Looks Like

A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

Skills Required

Aws (30% of roles) Azure (24% of roles) Docker (10% of roles) Gcp (17% of roles) Hugging Face (4% of roles) Javascript (6% of roles) Langchain (10% of roles) Prompt Engineering (15% of roles) Python (51% of roles) Pytorch (15% of roles)

Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.

Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.

Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

Compensation Benchmarks

AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($177K) sits 19% below the category median. Disclosed range: $129K to $225K.

Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.

Apple AI Hiring

Apple has 28 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Safety, AI Product Manager. Positions span Santa Clara, CA, US, Cupertino, CA, US, Seattle, WA, US. Compensation range: $225K - $381K.

Location Context

Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).

Career Path

Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.

From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.

If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.

What to Expect in Interviews

Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.

When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

AI Hiring Overview

The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.

The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

The AI Job Market Today

The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 424 roles with disclosed compensation, the median salary for AI Software Engineer positions is $219,250. Actual compensation varies by seniority, location, and company stage.
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
About 14% of the 3,708 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Apple is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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