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Senior Applied ML Researcher

Apple

Senior Applied ML Researcher

Apple

Cupertino, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Wellness benefits

Parental leave program

Learning and development stipend

Top Tier compensation with equity

Health, dental, and vision coverage

Remote work flexibility

Required Skills

Apache Spark

Python

Airflow

About the Role

We are seeking a Senior Applied ML Researcher to design, train, and deploy state-of-the-art models for visual and audio understanding. You will work on challenging problems at the intersection of computer vision, audio signal processing, and multimodal learning, enabling intelligent systems that can see, hear, and reason about the world.

You will collaborate closely with research scientists, engineers, and product teams to find novel applications of Deep Machine Learning capabilities to assist our creative user base. Your mission is to elevate the workflows of millions of creators by combining generative AI with Apple's human-centered design principles.

Responsibilities

  • Design and train deep neural networks for video, image, audio, and audio-visual tasks
  • Build models for audio-visual representation learning, cross-modal alignment, and fusion
  • Develop solutions for tasks such as:
  • Video understanding and temporal modeling
    • Audio-visual event detection
    • Speech, sound, and scene understanding
    • Multimodal classification, detection, and localization

Minimum Qualifications

  • MS in Computer Science, Machine Learning, or a related field, or equivalent practical experience
  • 4+ years of experience in deep learning or machine learning engineering
  • Strong expertise in deep neural networks and modern training workflows
  • 8+ years hands-on experience with computer vision and/or audio modeling
  • Proficiency in Python and deep learning frameworks (Py Torch preferred)
  • Solid understanding of linear algebra, probability, and optimization
  • Ability to build intuition from problem statement and translate to dataset requirement, neural network design and loss functions

Preferred Qualifications

  • PhD in computer science, machine learning, or a related field, or equivalent practical experience
  • Publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, etc.)
  • Experience with self-supervised or foundation model pre-training
  • Open-source contributions in vision, audio, or multimodal AI
  • Bonus: Experience with Objective-C and/or Swift for on-device deployment

Equal Opportunity

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.

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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