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Sr. Machine Learning Engineer, Siri Global

Apple

Sr. Machine Learning Engineer, Siri Global

Apple

Seattle, WA

·

On-site

·

Full-time

·

2w ago

Compensation

$201,300 - $302,200

Benefits & Perks

Healthcare

401(k)

Equity

Learning Budget

Healthcare

401k

Equity

Learning

Required Skills

Machine Learning

Deep Learning

LLMs

NLP

Java

C++

Objective-C

Swift

Python

TensorFlow

PyTorch

Join the Siri team at Apple! Build and contribute to a product and company that that is building products, personal devices, and software designed to enrich people's lives. Work on building and advancing the world's most popular intelligent assistant that helps millions of people get things done - just by asking.
Global Siri works to take Siri to the next level of intelligence and capabilities in all languages and markets. We build machine learning models, systems, and software that understands the intents hundreds of millions of users and their billions of requests to Siri, on Apple devices such as i Phone, i Pad, Apple Watch, Mac, Air Pods, Home Pod, Vision Pro and Apple TV. On the Global Scaling, Data, and Tools team, we work on ML modeling and algorithms, data platforms and technologies, and end-to-end ML product engineering to surprise and delight customers around the world in the languages that they speak.

Description:

We seek a Senior Machine Learning Engineer / Tech Lead who is passionate about collaborating across teams in Siri and Apple to design, build, and deploy world-class machine learning systems that help Siri best serve the needs of our users. In this role, you will work on creating and improving the accuracy, speed, reliability, and capability of Global Siri's models and systems. We are particularly interested in "full-stack" machine learning engineers with strong experience in research, software engineering, and have strong leadership potential.

You should be passionate about building outstanding products, and using the full spectrum of your skills to drive technical and organizational advancements. The ideal candidate is equally comfortable with the latest academic/research advancements in ML, LLMs, NLP, and related areas, diving into all parts of the full engineering/machine learning stack to diagnose user-facing issues and develop principled solutions, and deeply engaging in product metrics and goals with product managers, designers, and executives. Software engineering experience with both server-based and client-side (e.g. on-device) models is a definite asset. In this role, the ability to communicate complex technical ideas to diverse audiences, including research scientists, data scientists, engineers, designers, managers, and other stakeholders across Siri and Apple is also essential.

This position involves a wide variety of skills and innovation. In addition to your individual technical contributions, there are immense opportunities to multiply the impact those around you by mentoring, motivating and challenging engineers to deliver features at high quality. If you are looking for a role that is challenging, impactful, has immense growth opportunities, this role is for you.

Preferred Qualifications:

Experience in data science and analytics, including data annotation, statistical analyses, A/B testing, and/or conducting experiments and investigations in large-scale usage data environments

Self-starter with a proven ability to handle multiple projects with strict deadlines

Experience in the iOS development ecosystem (e.g. Swift, Objective-C, CoreML, or Siri Kit) is a plus

Experience in localization, internationalization, machine translation, or language technologies is an asset

Minimum Qualifications:

Master's or PhD degree in computer science, software engineering, machine learning, language technologies, or related fields; outstanding candidates with Bachelor's degrees and multiple years years of significant engineering/product experience will also be considered

10+ years of experience developing, shipping, and measuring industry-scale machine learning-based software systems; experience working on large-scale NLU systems a strong asset.

Experience as a senior engineer, tech lead, or engineering manager for a machine learning-based product, including mentoring other engineers, working with program and product managers, and communicating accomplishments, metrics, and challenges to cross-functional stakeholders and leaders

Expertise and experience in Large Language Models (LLMs) or other foundation models, ideally demonstrated through publications or shipping foundation model-based features and products.

Strong background in machine learning, deep learning, and foundation models, as demonstrated through top-tier publications and/or successful development of training data, models, or software in commercial machine learning systems.

Excellent software engineering skills: Proficiency in at least one object-oriented language (e.g. Java, C++, Objective-C, or Swift), scripting languages (e.g. Python, Ruby, bash), and deep learning/machine learning frameworks (e.g. Tensor Flow, Py Torch, or CoreML)

Outstanding problem solving, critical thinking, creativity, organizational, design, and interpersonal skills; ability to work with all levels of engineers, scientists, designers, and communicate effectively with management, leadership, and cross-functional partners

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 $201,300 and $302,200, 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

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