公司人數:40
資本額:55,000,000
地址:台北市松山區南京東路五段92號11F

洽詢電話:02-25288189#102 | HR

Viscovery (Visual Discovery) 成立於2013年,專注電腦視覺與深度學習的「Visual AI」技術,協助各垂直領域的領頭羊企業導入各式 AI 解決方案,是亞洲視覺辨識技術與影音大數據的領航公司。 Viscovery 研發中心設立於台北,由海外和本地對人工智慧、電腦視覺、深度學習、大數據領域專家組成,與全球頂尖的合作夥伴協作實現「AI+」。

營業項目

 Visual Recognition (圖片與影片辨識) - 自動化標示人臉、物件、場景、商標、動作、文字、情緒、抽象概念...等,將視覺檔案轉化成結構化大數據資訊並加以應用

 Visual Search (視覺搜索引擎) - 透過輸入視覺化的關鍵字,可透過複合式的標籤參數設定,精確搜尋圖片和影片畫面中的實際內容,便於尋找、管理、排列、過濾圖片和影片資料

 Visual Big Data (視覺大數據) - 透過視覺分析後產生的結構化影音大數據,可加以計算、歸納、總結、和探索影音內容的價值。

 Custom Recognition Model (客製化辨識模型) - 除了常見和通用的辨識模型外,Viscovery為企業開發客製化辨識模組,滿足特定的視覺辨識需求。

應徵須知

請透過創意引晴招募網站(https://www.viscovery.com/contact/)主動應徵,或透過104主動投遞履歷。

薪資福利

 優渥薪資、中秋獎金、年終獎金、績效獎勵
 績優員工認股、員工團體保險
 每月團隊聚餐,公司通通買單
 定期慶生會活動,滿滿的零食、飲料、歡樂,裝滿你的胃
 明亮開放現代的工作空間,吧檯咖啡區現磨咖啡喝不完



目前共有 3 個職缺類型

求才職稱資格條件工作內容待遇工作地點需求人數
Computer Vision Engineer
Knowledge
Must have:
• Proven knowledge in deep learning.
Nice to have:
• Solid background in machine learning.

Implement Experience
Must have:
• Python or C++ and with a desire to learn more.
• Experiences in developing computer vision algorithms.
• Experiences in developing algorithms in Linux environment.
Nice to have:
• Experiences in using TensorFlow, PyTorch and / or Caffe (or related tools).

Research Experiences
Must have:
• Experiences in computer vision.
Nice to have:
• Experiences in deep learning.
Best to have:
• Have deep learning related publications related to network architecture or computer vision.


Responsibilities
• Develop and deploy advanced vision and learning algorithms to solve industrial problems.
• Provide research consultancy on applied projects: determine the scope of the problem, the best place to apply machine learning, and evaluate different approaches.
• Interface with product teams to identify potential new problem areas for future projects.
• Experience in analyzing and extracting valuable information from million-scale business data
• Plan and execute cutting-edge research with focuses on object detection, image classification, and image retrievals.
• Report and present experimental results and research findings clearly and efficiently, both internally and externally.
面議 臺北市
松山區南京東路五段92號11F
3
Algorithm Back-End Engineer
1. Minimum 2 year experience with Python in Unix/Linux environments; C++ is a plus.
2. Familiar with at least one of the popular framework such as Caffe, Tensorflow, Pytorch and Onnx.
3. Strong software engineering fundamentals, including data structures, design patterns, testing, and debugging skills.
4. Having basic knowledge about computer vision is a plus.
5. Comfort with databases and performance analysis skills is a plus.
6. Having experience in virtual technology (Docker, VM) is a plus.
7. Experience with one or more continuous delivery tools (Jenkins, Ansible) is plus.


Responsibilities
Develop a flexible and scalable backend framework to accerlerate the AI models development process.
Co-work with and support team members to design system architecture, choose proper technologies and plan development.
Communicate friendly and professionally with scientists, engineers, product managers and other teams.
Explore challenging new areas and build high-quality software solutions for new and existing products.
Monitor, maintain and improve the quality of AI production system continuously.
Turn AI prototypes into products and deploy systems to the clients.
面議 臺北市
台北市松山區南京東路五段92號11樓
2
Computer Vision Scientist (AI/Deep Learning Expert)
Knowledge
• Proven knowledge in deep learning.
• Solid background in machine learning.

Implement Experience
• Python or C++ and with a desire to learn more.
• Experiences in developing computer vision algorithms (FITAMOS: Face/ Image/Text/Audio/Motion/Object/Scene)
• Experiences in developing algorithms in Linux environment.
• Experiences in using TensorFlow and / or Caffe (or related tools)

Research Experiences
• Experiences in computer vision (FITAMOS).
• Experiences in deep learning.
• Have deep learning related publications related to network architecture or computer vision (FITAMOS).


Responsibilities
· Perform research to make reinforcement learning more applicable to real world problems.
· Provide research consultancy on applied projects: determine the scope
of the problem, the best place to apply machine learning, and evaluate different approaches.
· Interface with product teams to identify potential new problem areas for future projects.
· Integrate new fundamental research ideas into applied projects.
· Collaborate with Software Engineers to design and run experiments, including designing and evaluating new algorithms as well as implementing known algorithms.
· Report and present experimental results and research findings clearly
and efficiently, both internally and externally.
面議 臺北市
台北市松山區南京東路五段92號11樓
2