refresh

트렌딩 기업

트렌딩

채용

JobsApple

Applied Machine Learning Research Engineer - Multimodal for Human Understanding

Apple

Applied Machine Learning Research Engineer - Multimodal for Human Understanding

Apple

Sunnyvale, CA

·

On-site

·

Full-time

·

2w ago

Compensation

$147,400 - $272,100

Benefits & Perks

Healthcare

401(k)

Equity

Learning Budget

Relocation Assistance

Healthcare

401k

Equity

Learning

Required Skills

Python

Machine Learning

PyTorch

JAX

Software Engineering

We're starting to see the incredible potential of multimodal foundation and large language models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Applied Machine Learning Research Engineer to join our team in the Video Computer Vision group and help us push the boundaries of human understanding. The Video Computer Vision org has pioneered human-centric real-time features such as FaceID, Face Kit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life.

Description:

In this role, you will drive ground breaking development at the intersection of AI, generative modeling, and computer vision. You will work across the full lifecycle-from foundational investigation to practical applications-designing, implementing, and evaluating novel algorithms and models.

Your primary focus will be human understanding, including human motion, activities, and representation learning. A major aspect of the role involves designing, implementing, evaluating and productizing ML systems capable of human and activity understanding.

This position offers a unique opportunity to innovate, build, and ship: you will take your conceptual ideas to products that reach millions of users worldwide. You will collaborate with a diverse group of experts-research scientists, ML engineers, software engineers, data scientists, human-interface designers, and domain specialists-working in an environment that values experimentation, ownership, and continuous learning.

By staying at the forefront of advancements in AI, machine learning, and computer vision, you will play a direct role in driving innovation, influencing the evolution of Apple products, and meaningfully enhancing user experience on a global scale.

Preferred Qualifications:

Hands-on experience training and deploying production-grade ML models.

Experience developing multimodal LLMs or generative models.

Production-level experience with a compiled language (e.g., Swift, C++).

Expertise in one or more areas: computer vision, machine learning, multimodal LLMs, Reinforcement Learning, Agentic AI.

PhD in Computer Science, Electrical Engineering, or a related field with a focus on computer vision, machine learning, or multimodal systems.

Demonstrated problem-solving ability, strong sense of ownership and product shipment.

Minimum Qualifications:

Strong experience developing machine learning models.

Proficiency in Python and solid software engineering fundamentals.

Experience with at least one deep learning framework (e.g., Py Torch, JAX, or equivalent).

Master's degree in Computer Science or a related field, plus 3 years of relevant industry experience.

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 $147,400 and $272,100, 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.

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

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