招聘

Sr. ML Infrastructure Engineer, Siri Runtime Systems and Interaction
Seattle, WA
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Learning and development stipend
•Annual team offsites
•Flexible PTO policy
•Wellness benefits
Required Skills
Python
Apache Spark
TensorFlow
Apple
- Siri Data and Tooling Engineer
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Do you want to make Siri and Apple products more intelligent for our users? The Siri Attention and Invocation team is the front door to Siri. We make sure all our Apple costumers can invoke Siri how and when they want to.
Description
As part of the Data and Tooling team, you will help us create the data and infrastructure ecosystem needed to support our ML development and continuously improve our features.
We take full end-to-end ownership of our services and data products, driving them through every stage meticulously, encompassing conception, design, implementation, deployment, and maintenance. As a result, each one of us takes our responsibilities seriously. In this team, you'll have the opportunity to work on complex problems in close partnership with our ML Modeling teams, Infrastructure, Software, Hardware and Operations.
Minimum Qualifications
- At least 4+ years of relevant industry experience with the following:
- Strong background in computer science: algorithms, data structures and system design
- In-depth knowledge and experience with the following technologies: Python, Docker, Cloud Infrastructure, Spark
- Expertise in developing and debugging software service stacks
- Excellent interpersonal skills able to work independently as well as cross-functionally
- Bachelors degree in Computer Science, Engineering, or related discipline, or equivalent industry experience
Preferred Qualifications
- Familiar with one of the popular ML Frameworks like Pytorch, Tensorflow
- Familiar with workflow orchestrators like Airflow or Kubeflow
- Developed tools and services to optimize ML systems beyond model selection
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
PublicA 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
L2
L3
L4
L5
L6
L2 · Cybersecurity Analyst L2
0 reports
$169,000
total / year
Base
$67,600
Stock
$84,500
Bonus
$16,900
$118,300
$219,700
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
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