CakeResume 找人才

進階搜尋
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
United States
Avatar of Mike Garuccio.
Site Reliability Engineer
超過一年
move into a Site Reliability Engineering role with more focus on CI/CD and containerization. Systems Engineer Cleveland, OH [email protected] github.com/mgaruccio linkedin.com/in/mgaruccio Skills Platforms Linux Windows VMWare AWS(some familiarity) Azure(some familiarity) Languages Powershell(deep knowledge) Javascript Bash Python(some familiarity) Ruby(some familiarity) Tools vRealize Orchestrator Appveyor Git Docker Kubernetes Experience Systems Engineer - Expedient, JanPresent Served as liaison between automation and service delivery teams. Helped to complete a project which automated a complete delivery process, freeing up engineers to spend time
Automation
Linux
Powershell
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
6 到 10 年
Avatar of 李岳峰.
Avatar of 李岳峰.
創辦人 @酷喬伊科技有限公司
2020 ~ 現在
Python developer
一個月內
的新創產品 Demo,是在低階筆記型電腦上處理並呈現影像辨識結果。 # PyTorch # Onnx # OpenCV # Pillow # Flask # FastAPI # uvicorn # Subprocess # SQLite3 # PyQt5 # Command # Powershell AI Bottle Recycle 這個案件是一位以色列人的需求,他想用影像辨識來呈現無人回收機器,當時做的是一個 Demo。 這裡用了第三方套
PyTorch
Python
PostgreSQL
就職中
目前沒有興趣尋找新的機會
全職 / 對遠端工作有興趣
4 到 6 年
Fu Jen Catholic University
Major, Optical Physics, Minor, Finance and international business

最輕量、快速的招募方案,數百家企業的選擇

搜尋履歷,主動聯繫求職者,提升招募效率。

  • 瀏覽所有搜尋結果
  • 每日可無限次數開啟陌生對話
  • 搜尋僅開放付費企業檢視的履歷
  • 檢視使用者信箱 & 電話
搜尋技巧
1
嘗試搜尋最精準的關鍵字組合
資深 後端 php laravel
如果結果不夠多,再逐一刪除較不重要的關鍵字
2
將須完全符合的字詞放在雙引號中
"社群行銷"
3
在不想搜尋到的字詞前面加上減號,如果想濾掉中文字,需搭配雙引號使用 (-"人資")
UI designer -UX
免費方案僅能搜尋公開履歷。
升級至進階方案,即可瀏覽所有搜尋結果(包含數萬筆覽僅在 CakeResume 平台上公開的履歷)。

職場能力評價定義

專業技能
該領域中具備哪些專業能力(例如熟悉 SEO 操作,且會使用相關工具)。
問題解決能力
能洞察、分析問題,並擬定方案有效解決問題。
變通能力
遇到突發事件能冷靜應對,並隨時調整專案、客戶、技術的相對優先序。
溝通能力
有效傳達個人想法,且願意傾聽他人意見並給予反饋。
時間管理能力
了解工作項目的優先順序,有效運用時間,準時完成工作內容。
團隊合作能力
具有向心力與團隊責任感,願意傾聽他人意見並主動溝通協調。
領導力
專注於團隊發展,有效引領團隊採取行動,達成共同目標。
超過一年
United States
專業背景
目前狀態
求職階段
專業
產業
工作年資
管理經歷
技能
語言能力
求職偏好
希望獲得的職位
預期工作模式
期望的工作地點
遠端工作意願
接案服務
學歷
學校
主修科系
列印
WeChat Image_20170718170420.jpg

Chen LIU

Software Engineer at Microsoft 


[email protected]

(+86) 15002933895 

(+86) 59165119 

Beijing, China

Skills


C/C++

Cosmos/C#/CX/Powershell/SQL

Algorithem/Data Structure/Design Pattern

Creative problem solving

Communication and Collaboration Skills

Education

Xidian University  (2011 - 2014)

Master's Degree - Computer Software and Theory


Northwest University  (2007 - 2011)

Bachelor's Degree - Computer Science and Technology

Experience

CHS Auto Correction on Mobile Device - Apr. 2014 - Jul. 2014

  • A model could "guess" what key user may want to input on mobile device. 
  • The SIP(software input panel) on mobile is very small and user easily to mistype the key. Auto-Correction model is designed to address this problem. 
  • To achieve this goal, I set up this model based on some statistics result: the model was built based on TTR statistical data which record the position information of every user's input. Given a target key (a-z) on the SIP, I calculate the probabilities of every surrounding keys. I also give this model some capability of self-adaption to serve people who have different typing behaviour. 
  • This feature is default on in every windows mobile devices since Windows 10. Our telemetry data shows that this model improves the user's editing behaviour: higher selection rate and input speed, fewer deleting action.

CHS Shape Writing on Mobile Device - Aug. 2014 - Dec. 2014

  • Code name "Blue Bird", provide a new input experience. User could swipe the input keys on the SIP to finish the input. It is different with hand writing, shape writing need to swipe all the keys on the Qwerty SIP. A group of people prefer to input via shape writing and they feel input this way could largely improve their typing speed. 
  • Chinese shape writing is different with Latin shape writing and it's more complex that Latin one. Chinese shape writing could input a word, a phrase and a sentence with only one gesture. 
  • This is the first version of CHS shape writing, I have no data to support such model. Thus, I build a rule-based model as our V1.0 Shape writing. The model use Fréchet Distance to calculate the position similarity between user's gesture and standard one. Using cosine-based vector to calculate the shape similarity. Gain the probabilities of each calculated words path, put penalty to each syllable and do some pruning, finally get the ranked best path and phrases as the output to users.

Windows 10 upgrade in China - Dec. 2014 - Oct. 2015

  • This is the top priority project in WDGC(Windows Device Group China) at that time. We called up as a virtual team to work together. The goal of this project is: the more devices upgrade to Windows 10 in China, the more we achieved. 
  • We cooperated with some local influential companies, like Tencent, Qihu360 and Baidu to help to promote the Windows 10. Basically, we provide the core solution and APIs to our partners, and they provide the user experience. 
  • Besides, we also need the manner to control the whole upgrade process, like enable/disable one partner, allot upgrade quota and online key distribution. To achieve this, I set up a azure cloud service to control the whole upgrade to make it safer and easily control. At last, I need to build a telemetry system in this whole procedure, not only collecting the numbers/categories, but also the dump/log files which could help us analyze the failure. 
  • This was a challenging project and very different with other projects we experienced. We all learn a lot from it.

Taihang Project - Oct. 2014 - Nov. 2015

  • Code name "Taihang" is an updated version of "Kunlun". This is the core component of an IME, data source(DS). The DS is in charge of the conversion from Pinyin letters to Chinese characters. 
  • Before this project, we have two version of the main DS, one is in mobile and another is in desktop. This increase the maintaining and development cost. "Taihang" project is target to converge the DS from different planform and apply to all SKUs. 
  • The challenge here is: 1) apply one DS to different input stacks; 2) performance tuning; 3) feature parallel.

TSF2.0 IME stabilization - Dec. 2015 - Apr. 2016

  • In this period, I mainly focused on the toughest issues in our products, most of them are performance or compatibility issues. This kind of bugs don't have solid reproduce steps or dump file to help analysis, basically, these came from user's feedback. 
  • To address them, need to add data points to collect more information, flight the build contained these data point and analysis the collected data to approach the root cause. 
  • Most of the issues were hidden in the system layer and finally, we addressed the pain points for users.

Live Sticker - Apr. 2016 - Oct. 2016

  • Live sticker is a brand new concept to our IME which including the rich content and online service. 
  • Live Sticker provide to user the ability to input images(GIF, PNG, etc.) based on the context. IME retrieve the context from the edit control and query the online service to get the most popular images associate with the query string, display the result to user and insert into the edit control by clicking the picture. 
  • Additionally, to minimize the risk of this new thing, I add the cloud control to give us the capability to enable/disable this feature on specific applications.

TSF3.0 IME - Oct. 2016 - Nov. 2017

  • TSF(Text Service Frame) is the layer between application, system and IME. Currently, Microsoft Chinese IME are built based on TSF2.0 on desktop and based on TSF2.9 on Mobile (close to TSF3.0, but not exact same). TSF3.0 is the next version of input stack and we are moving to this new framework. Our team is the pioneer on this because of some historical reasons and I was the driver on this project. 
  • A lot of communication across teams to discuss the design of the API, framework and dependencies, like what's the API surface looks like, how components communicate to each other, what's is the best sequences for each API call, etc. I need to build prototypes and verify different design to identify the potential risk earlier. Design and implement the API, host the IME, deploy it to different SKUs and make it self-hostable. We are currently at this stage.

Bing Advertisement Delivery Engine - Nov. 2017 - Present

  • Delivery Engine (DE) is a large scale system including thousands of machines with different roles. It is the core component in the Bing Ads system. It's responsible for select the best ads which fits the user's queries. 
  • Building the distribution system which have the capability to handle the large amount of queries within quite low latency and stable performance. 
  • Design and implement advertiser and algorithm feature with high quality.
  • Profiling and optimizing the system performance, including the memory, latency and capacity.
  • Design and implement the machine function to calculate the relevance between query and keyword as a platform to improve the latency and accuracy.
  • Re-architect the "dynamic ads" workflow which doubles the system capacity and reduce the latency.
  • Design and implement the "Vertical ads" workflow to provide brand new user experience on Bing ads for Event, Tours and activities scenarios.

Self-Evaluation

  • Enjoy learning new things and taking challenge
  • Have passion on technology and learn quickly
  • Happy to sharing and help others

履歷
個人檔案
WeChat Image_20170718170420.jpg

Chen LIU

Software Engineer at Microsoft 


[email protected]

(+86) 15002933895 

(+86) 59165119 

Beijing, China

Skills


C/C++

Cosmos/C#/CX/Powershell/SQL

Algorithem/Data Structure/Design Pattern

Creative problem solving

Communication and Collaboration Skills

Education

Xidian University  (2011 - 2014)

Master's Degree - Computer Software and Theory


Northwest University  (2007 - 2011)

Bachelor's Degree - Computer Science and Technology

Experience

CHS Auto Correction on Mobile Device - Apr. 2014 - Jul. 2014

  • A model could "guess" what key user may want to input on mobile device. 
  • The SIP(software input panel) on mobile is very small and user easily to mistype the key. Auto-Correction model is designed to address this problem. 
  • To achieve this goal, I set up this model based on some statistics result: the model was built based on TTR statistical data which record the position information of every user's input. Given a target key (a-z) on the SIP, I calculate the probabilities of every surrounding keys. I also give this model some capability of self-adaption to serve people who have different typing behaviour. 
  • This feature is default on in every windows mobile devices since Windows 10. Our telemetry data shows that this model improves the user's editing behaviour: higher selection rate and input speed, fewer deleting action.

CHS Shape Writing on Mobile Device - Aug. 2014 - Dec. 2014

  • Code name "Blue Bird", provide a new input experience. User could swipe the input keys on the SIP to finish the input. It is different with hand writing, shape writing need to swipe all the keys on the Qwerty SIP. A group of people prefer to input via shape writing and they feel input this way could largely improve their typing speed. 
  • Chinese shape writing is different with Latin shape writing and it's more complex that Latin one. Chinese shape writing could input a word, a phrase and a sentence with only one gesture. 
  • This is the first version of CHS shape writing, I have no data to support such model. Thus, I build a rule-based model as our V1.0 Shape writing. The model use Fréchet Distance to calculate the position similarity between user's gesture and standard one. Using cosine-based vector to calculate the shape similarity. Gain the probabilities of each calculated words path, put penalty to each syllable and do some pruning, finally get the ranked best path and phrases as the output to users.

Windows 10 upgrade in China - Dec. 2014 - Oct. 2015

  • This is the top priority project in WDGC(Windows Device Group China) at that time. We called up as a virtual team to work together. The goal of this project is: the more devices upgrade to Windows 10 in China, the more we achieved. 
  • We cooperated with some local influential companies, like Tencent, Qihu360 and Baidu to help to promote the Windows 10. Basically, we provide the core solution and APIs to our partners, and they provide the user experience. 
  • Besides, we also need the manner to control the whole upgrade process, like enable/disable one partner, allot upgrade quota and online key distribution. To achieve this, I set up a azure cloud service to control the whole upgrade to make it safer and easily control. At last, I need to build a telemetry system in this whole procedure, not only collecting the numbers/categories, but also the dump/log files which could help us analyze the failure. 
  • This was a challenging project and very different with other projects we experienced. We all learn a lot from it.

Taihang Project - Oct. 2014 - Nov. 2015

  • Code name "Taihang" is an updated version of "Kunlun". This is the core component of an IME, data source(DS). The DS is in charge of the conversion from Pinyin letters to Chinese characters. 
  • Before this project, we have two version of the main DS, one is in mobile and another is in desktop. This increase the maintaining and development cost. "Taihang" project is target to converge the DS from different planform and apply to all SKUs. 
  • The challenge here is: 1) apply one DS to different input stacks; 2) performance tuning; 3) feature parallel.

TSF2.0 IME stabilization - Dec. 2015 - Apr. 2016

  • In this period, I mainly focused on the toughest issues in our products, most of them are performance or compatibility issues. This kind of bugs don't have solid reproduce steps or dump file to help analysis, basically, these came from user's feedback. 
  • To address them, need to add data points to collect more information, flight the build contained these data point and analysis the collected data to approach the root cause. 
  • Most of the issues were hidden in the system layer and finally, we addressed the pain points for users.

Live Sticker - Apr. 2016 - Oct. 2016

  • Live sticker is a brand new concept to our IME which including the rich content and online service. 
  • Live Sticker provide to user the ability to input images(GIF, PNG, etc.) based on the context. IME retrieve the context from the edit control and query the online service to get the most popular images associate with the query string, display the result to user and insert into the edit control by clicking the picture. 
  • Additionally, to minimize the risk of this new thing, I add the cloud control to give us the capability to enable/disable this feature on specific applications.

TSF3.0 IME - Oct. 2016 - Nov. 2017

  • TSF(Text Service Frame) is the layer between application, system and IME. Currently, Microsoft Chinese IME are built based on TSF2.0 on desktop and based on TSF2.9 on Mobile (close to TSF3.0, but not exact same). TSF3.0 is the next version of input stack and we are moving to this new framework. Our team is the pioneer on this because of some historical reasons and I was the driver on this project. 
  • A lot of communication across teams to discuss the design of the API, framework and dependencies, like what's the API surface looks like, how components communicate to each other, what's is the best sequences for each API call, etc. I need to build prototypes and verify different design to identify the potential risk earlier. Design and implement the API, host the IME, deploy it to different SKUs and make it self-hostable. We are currently at this stage.

Bing Advertisement Delivery Engine - Nov. 2017 - Present

  • Delivery Engine (DE) is a large scale system including thousands of machines with different roles. It is the core component in the Bing Ads system. It's responsible for select the best ads which fits the user's queries. 
  • Building the distribution system which have the capability to handle the large amount of queries within quite low latency and stable performance. 
  • Design and implement advertiser and algorithm feature with high quality.
  • Profiling and optimizing the system performance, including the memory, latency and capacity.
  • Design and implement the machine function to calculate the relevance between query and keyword as a platform to improve the latency and accuracy.
  • Re-architect the "dynamic ads" workflow which doubles the system capacity and reduce the latency.
  • Design and implement the "Vertical ads" workflow to provide brand new user experience on Bing ads for Event, Tours and activities scenarios.

Self-Evaluation

  • Enjoy learning new things and taking challenge
  • Have passion on technology and learn quickly
  • Happy to sharing and help others