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Full-Stack Software Engineer

Apple

Full-Stack Software Engineer

Apple

San Diego, CA

·

On-site

·

Full-time

·

4d ago

At Apple, great ideas grow when diverse perspectives come together. Every product, service, and experience we create is built by people who care deeply about quality, collaboration, and learning. When we bring everybody in, we do the best work of our lives and here, you'll do more than join something. You'll add something.
We are looking for a Full-Stack Software Engineer to join the VEDI ML Tools & Workflows team. This role is ideal for engineers early in their career who are excited to work at the intersection of machine learning infrastructure, data systems, and intuitive developer-facing tools.

You'll help build and evolve internal platforms that support large-scale AI training and evaluations from backend services and APIs to modern web interfaces used by ML researchers and engineers every day.

Description:

As a Full Stack Engineer, you will bridge the gap between complex machine learning infrastructure and intuitive user experiences, developing the tools that allow researchers to interact with, visualize, and optimize multimodal training at scale. You'll work across the stack to turn complex ML workflows into approachable, reliable software.","responsibilities":"Build full-stack tools using Python (FastAPI / Flask / Django) and modern React to support ML workflows and internal platforms

Develop backend services and APIs that orchestrate data flows, training jobs, and evaluation pipelines

Create clear, usable web interfaces for monitoring model performance, dataset status, and experiment results

Collaborate closely with ML researchers, data engineers, and designers to translate real needs into production-quality tools

Contribute to scalable systems handling large datasets (text, image, audio, video) in distributed environments

Write clean, maintainable code and participate in thoughtful code reviews across the stack

Learn and grow with mentorship, design reviews, and exposure to production ML systems at scale

Preferred Qualifications:

Master's degree in Computer Science, Software Engineering, or related field

Experience using AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, internal tools) for tasks like: Prototyping and iterating on ideas, Improving test coverage, Debugging and refactoring code, Learning new frameworks or domains

Understanding of software engineering best practices (testing, version control, code reviews)

Exposure to machine learning concepts or libraries (e.g., Py Torch)

Experience with Docker, Kubernetes, or CI/CD pipelines

Interest in data visualization or dashboard development

Familiarity with distributed systems, data pipelines, or MLOps concepts

Experience with 3D or advanced visualization (Three.js, WebGL, etc.)

Strong communication skills and comfortable working in a collaborative, cross-functional team

Minimum Qualifications:

Bachelor's degree in Computer Science, Software Engineering, or related field and 3+ years of relevant industry experience (or equivalent practical experience)

Experience building web applications using Python and a modern backend framework (FastAPI, Flask, or Django)

Experience with React and modern JavaScript/TypeScript concepts

Familiarity with REST APIs, databases (SQL or NoSQL), and data-driven applications

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 .

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 $139,500 and $258,100, 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.

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About Apple

Apple

Apple

Public

A technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.

10,001+

Employees

Cupertino

Headquarters

$3.5T

Valuation

Reviews

4.0

10 reviews

Work Life Balance

4.0

Compensation

4.2

Culture

3.8

Career

3.5

Management

3.2

75%

Recommend to a Friend

Pros

Great coworkers and people

Excellent benefits and perks

Fast-paced and engaging work environment

Cons

High expectations and pressure

Management quality varies

Limited career progression opportunities

Salary Ranges

17,968 data points

L2

L3

L4

L5

L6

L2 · Business Analyst L2

0 reports

$114,215

total / year

Base

$45,686

Stock

$57,108

Bonus

$11,422

$79,951

$148,480

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Duration

28-42 weeks

Offer Rate

20%

Experience

Positive 20%

Neutral 40%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit