
Life's more fun when you live in the moment.
Spectacles Student Worker- Computer Vision Engineering
必須スキル
Python
Machine Learning
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.
The Spectacles team is pushing the boundaries of technology to bring people closer together in the real world. Our fifth-generation Spectacles, powered by Snap OS, showcase how standalone, see-through AR glasses make playing, learning, and working better together.
Snap’s camera supports real friendships through visual communication, self expression and storytelling. Moving forward, our camera will play a transformative role in how people experience the world around them, combining what they see in the real world, with all that’s available to them in the digital world.
We are looking for a Computer Vision Engineering PhD or MS student to join our student worker program at Snap Inc!
What you’ll do
The Spectacles student employment is a full-time position for the duration of 3 to 6 months. We aim to offer students industry exposure and hands-on experience. Your start date is flexible and can be arranged together with the hiring manager. You will:
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Research and develop advanced computer vision algorithms and enhance performance for Spectacles-specific challenges.
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Implement and optimize computer vision technologies onto Spectacles.
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Write clean and modular code. Test and iterate on algorithms/models to ensure robustness and efficiency.
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Research novel CV/AR methodologies and publish results (Optional) or contribute to patents, bridging academic innovation and product development.
Knowledge, Skills, & Abilities
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Solid foundation in Computer Vision such as camera models, multi-view geometry and transformations
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Solid Math background with understanding of 3D geometry, trigonometry and linear algebra
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Ability to understand, debug and improve existing code as well as develop new algorithms using advanced computer vision and machine learning techniques.
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Ability to collaborate with other engineers and across different teams
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Minimum Qualifications
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Currently enrolled in a MS or PhD program in a technical field, such as Computer Science, Electrical Engineering, or a related field
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You must be legally permitted to work in Austria as a student
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Proficiency in programming Python/C++
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Research experience with machine learning / computer vision approaches, in one or more of the following areas: Camera Calibration, Sensor Calibration and Fusion, Visual Inertial System, Hand Tracking, Object Tracking, Visual SLAM, Bundle Adjustment, Depth Estimation, 3D Scene Reconstruction, Semantic Segmentation, Motion Generation, Stable Diffusion
Preferred Qualifications
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PhD candidate in related fields (Computer Vision, Machine Learning, Robotics etc.)
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Experience with integrating Machine Learning models into Augmented Reality solutions
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Experience with 3D engines, e.g. Lens Studio, Blender, Unity, Unreal Engine
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Have at least one first-author publication in a top conference (CVPR, NeurIPS, ECCV, ICCV, etc.).
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
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Snap Inc.について

Snap Inc.
PublicSnap Inc. is an American technology company, founded on September 16, 2011, by Evan Spiegel, Bobby Murphy, and Reggie Brown, based in Santa Monica, California. The company developed and maintains technological products and services, namely Snapchat, Spectacles, Bitmoji, and SnapBoost.
5,001-10,000
従業員数
Santa Monica
本社所在地
$15B
企業価値
レビュー
10件のレビュー
3.8
10件のレビュー
ワークライフバランス
2.5
報酬
3.5
企業文化
3.2
キャリア
3.8
経営陣
2.8
65%
知人への推奨率
良い点
Innovative and interesting projects
Great team culture and supportive colleagues
Good learning opportunities and growth
改善点
Long hours and high workload
Work-life balance challenges
High expectations and tight deadlines
給与レンジ
40件のデータ
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Scientist
2件のレポート
$130,000
年収総額
基本給
$100,000
ストック
-
ボーナス
-
$125,681
$130,000
面接レビュー
レビュー5件
難易度
3.2
/ 5
期間
14-28週間
体験
ポジティブ 0%
普通 80%
ネガティブ 20%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
最新情報
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