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职位Apple

AIML - Sr Machine Learning Engineer - Data and ML Innovation

Apple

AIML - Sr Machine Learning Engineer - Data and ML Innovation

Apple

Cupertino, CA

·

On-site

·

Full-time

·

3d ago

Would you like to be a part of Apple's AI and Machine Learning org, where we encourage and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities? The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices for real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to build for billions of users worldwide.

Description

As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem.

Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.

YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING:

Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification.

Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps.

Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges.

Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions.

Preferred Qualifications

Deep understanding of multi-modal foundation models.

Staying up-to-date with emerging trends in generative AI and multi-modal LLMs.

The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams.

Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.).

Track records of adopting ML to solve cross-disciplinary problems.

Minimum Qualifications

Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning.

Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like Py Torch, Tensor Flow, or JAX (one of).

5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.'

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.

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关于Apple

Apple

Apple

Public

Apple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.

10,001+

员工数

Cupertino

总部位置

$3.5T

企业估值

评价

3.9

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.8

职业发展

3.5

管理层

3.2

72%

推荐给朋友

优点

Great benefits and compensation

Talented colleagues and supportive teams

Learning opportunities and mentorship

缺点

Work-life balance challenges

High stress and pressure

Fast-paced environment

薪资范围

11,365个数据点

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0份报告

$121,979

年薪总额

基本工资

-

股票

-

奖金

-

$103,682

$140,276

面试经验

3次面试

难度

3.3

/ 5

时长

28-42周

录用率

33%

体验

正面 33%

中性 0%

负面 67%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience