
Think Different.
Deep Learning Engineer - Perception Algorithms
Required skills
Machine Learning
Do you have a passion for deep learning and computer vision problems? We are looking for someone who thrives on collaboration and wants to push the boundaries of what is possible today!
Join our team of committed deep learning engineers in the Video Computer Vision group! We are a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision, Machine Perception, and Generative technologies across Apple products. Our shipped technologies power features in ARKit, Measure App, Room Scan, Accessibility, and multiple Vision Pro features.
As a member of the Video Computer Vision group you will develop new technologies in the area of scene understanding and for Apple's next generation products.
Description:
We are looking for a skilled Deep Learning Engineer for our team. In this role, you will perform research and development work to design algorithms for challenging real world problems in the domain of scene understanding.","responsibilities":"Data curation for improving performance on perception tasks (training and evaluation sets).
Research, design, train, and evaluate machine learning/deep learning algorithms to address product goals.
Benchmark and analyze machine learning/deep learning algorithms to understand limitations.
Optimize algorithms for real time and low power constraints.
Support algorithm integration into Apple products and ensure quality user experience.
Collaborate with teams across Apple with multidisciplinary skills.
Preferred Qualifications:
PhD degree with focus on machine learning, computer vision, robotics or MS with a comparable industry career of 3+ years.
Consistent track record of researching, inventing and/or shipping advanced machine learning algorithms.
Experience in language-guided image understanding tasks e.g. open-vocabulary image classification, language-guided visual grounding, open-vocabulary semantic segmentation, etc.
Experience with designing and training with pipelines which consume large (billion scale) data for training efficient vision language models for edge-devices. This includes data curation for training vision language models, writing efficient data loading pipelines, utilizing distributed GPU training framework.
Experience with advanced task-specific quality optimization techniques (few-shot learning, meta-learning, domain adaptation, knowledge-distillation, fine-grained learning) for improving network performance and handling specific failure cases (long-tailed distributions/under-represented classes) for downstream tasks.
Experience in designing and optimizing network towards inference efficiency.
Strong coding skills in ObjectiveC.
Excellent communication and collaboration skills.
Minimum Qualifications:
BS in Computer Science or related field with a minimum of 3 years of relevant industry experience.
Experience in designing and training deep learning networks for image understanding tasks, e.g. image classification, object detection, semantic segmentation, panoptic segmentation, etc.
Experience in developing downstream perception algorithms with vision-language models, e.g. CLIP
Solid mathematical foundation of machine learning and deep learning techniques.
Strong coding skills in python (with pytorch) and C/C++. Solid mathematical foundation of machine learning and deep learning techniques.
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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About Apple

Apple
PublicApple 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+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
10 reviews
3.9
10 reviews
Work-life balance
2.8
Compensation
4.2
Culture
3.6
Career
3.4
Management
3.2
72%
Recommend to a friend
Pros
Great benefits and compensation
Talented colleagues and supportive teams
Learning opportunities and mentorship
Cons
Work-life balance challenges
Fast-paced and high-stress environment
Long hours and heavy workload
Salary Ranges
11,365 data points
Junior/L3
L2
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
L3
L4
L5
Junior/L3 · Data Scientist ICT2
0 reports
$121,979
total per year
Base
-
Stock
-
Bonus
-
$103,682
$140,276
Interview experience
3 interviews
Difficulty
3.3
/ 5
Duration
28-42 weeks
Offer rate
33%
Experience
Positive 33%
Neutral 0%
Negative 67%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
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