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Senior Machine Learning Engineer - Maps Traffic

Apple

Senior Machine Learning Engineer - Maps Traffic

Apple

Cupertino, CA

·

On-site

·

Full-time

·

2w ago

Compensation

$181,100 - $318,400

Benefits & Perks

Healthcare

401(k)

Equity

Learning Budget

Healthcare

401k

Equity

Learning

Required Skills

Machine Learning

Java

Scala

C++

SQL

NoSQL

Algorithms

When will rush hour start tomorrow? How long will it take for a traffic jam to clear up? We believe these questions are important to millions of people around the world, and we strive to answer them for you!
Helping people navigate around the globe is one of our primary functions here on the Apple Maps team. We are the traffic team at Apple Maps and our main mission is to deliver accurate travel times and incidents for the world in realtime. We want to make sure that our recommendations are as accurate and responsive to external factors as possible. We are looking to hire a Software Engineer to help us ensure that Apple Maps provides the most accurate and reliable navigation experience possible, while handling and working with high volumes of live and historical data.

As our team member, your work will directly impact how people move through their world, making their journeys more efficient and enjoyable

Description:

Our team drives the designs, crafts the solutions, and evaluates the systems that accurately process massive streams of location data. As part of our team, you will enhance the quality of our traffic solutions, invent features and functionality, all while improving the experiences of millions of users each and every single day. As a traffic software engineer, you will be a key member of our team designing, implementing, and evaluating models which process huge amounts of GPS and sensor data. You will make substantial contributions towards the scalability and resilience of our core systems to ensure they work seamlessly across different execution contexts from real-time analysis to batch processing. Your role will expand into data science and ML as we build innovative solutions for future traffic challenges. You'll work as part of a dynamic, multi-functional team of software and ML engineers, data scientists, and traffic experts to help set the future direction of the product. We are a distributed team based in different parts of the world, and as such we support a production system with occasional work outside standard business hours.

Preferred Qualifications:

MS/PhD or equivalent experience in Computer Science or a quantitative field

Proven experience in working with very large-scale real-time data

Experience in building large-scale data pipelines, possibly using Spark or Flink

Experience with machine learning frameworks (e.g. Py Torch, Tensor Flow) and model deployment a plus

Aptitude for learning independently; prototyping and proposing new software designs as a philosophy for delivering successful deployments

Experience with working on cloud-based infrastructure (preferably Kubernetes)

Experience with location data a plus

Front-end experience a plus

Minimum Qualifications:

BS in Computer Science or a quantitative field plus at least 8 years of production level development and machine learning experience.

Programming experience with a typed-language like Java, Scala and/or C++

Proficiency in working with SQL/NoSQL databases

Strong background in algorithms and ability to tackle complex challenges, think critically, and develop innovative algorithms

Excellent communication skills and ability to adapt quickly in a dynamic, fast-paced environment

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 $181,100 and $318,400, 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