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AIML - Machine Learning Researcher, MLR

Apple

AIML - Machine Learning Researcher, MLR

Apple

Seattle, WA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Learning and development stipend

Annual team offsites

Flexible PTO policy

Health, dental, and vision coverage

Top Tier compensation with equity

Parental leave program

Required Skills

SQL

Airflow

TensorFlow

About the Role

Play a part in building the next revolution in machine learning technology. We're looking for passionate researchers to work on ambitious, curiosity-driven, long-term research projects. In this role, you'll have the opportunity to work on innovative foundational research in machine learning. As a member of the team, you will be inspired by a diversity of challenging problems, collaborate with world-class machine learning engineers and researchers to impact the future of Apple products, and publish some of your results in high-quality scientific venues.

Description

You should have a strong research background in machine learning or related fields, with a proven record of publications in leading machine learning conferences and journals. In this role, you will have the opportunity to define and pursue a research agenda focused on solving fundamental problems related to data-centric ML and AI agents, such as synthetic data generation, enhancing planning and reasoning capabilities of ML models. You will focus on producing high-quality, reproducible research and advancing our understanding of these areas through rigorous experimentation and close collaboration with colleagues. You will also develop high-quality code, provide technical mentorship, and prepare publications and presentations for top-tier venues. Additionally, you will have opportunities to collaborate with broader teams across Apple.

Minimum Qualifications

  • Demonstrated expertise in machine learning research
  • Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ECCV, ACL, EMNLP, NAACL, etc.)
  • Strong hands-on experience working with Python and deep learning toolkits such as Py Torch
  • Strong mathematical skills in linear algebra and statistics

Preferred Qualifications

  • Ability to formulate a research problem and design, experiment, implement, and communicate solutions
  • Ability to work in a diverse, collaborative environment
  • High-quality open-source contributions to related projects
  • PhD or equivalent practical experience in Computer Science or a related technical field
  • Strong presentation skills for internal and external communications

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

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0 reports

$121,979

total / year

Base

-

Stock

-

Bonus

-

$103,682

$140,276

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