Machine Learning Engineer, Space Maps

Woven Planet

  • Full Time

ABOUT WOVEN PLANET GROUP
Woven Planet Group (Woven Planet) represents a carefully curated blend of expertise and resources dedicated to bringing the vision of “Mobility to Love, Safety to Live” to life. Through innovations and investments in automated driving, robotics, smart cities, and more, we are transforming how humankind lives, works, and moves. We exist to design, build, and deliver secure, connected, and sustainable mobility solutions that benefit all people worldwide. Founded in 2018 as Toyota Research Institute – Advanced Development (TRI-AD), Woven Planet is composed of four complementary companies: Woven Planet Holdings, Woven Core, Woven Alpha, and Woven Capital.

Visit us to learn more: https://www.woven-planet.global/

TEAM
The Automated Mapping Platform team is responsible for developing a new high definition mapping cloud platform by integrating sensor data from vehicles and global imagery from satellites. It is an open software platform based on a contribution model: participating developers accept that vehicles deploying their application or software supply anonymized sensor data to the platform. In return, every developer has easy, safe, open and sustainable access to high definition maps from across industries, fleets and car makers. One-stop-shop open APIs that allow developers to focus on building software. No need to worry about specific map implementations and maintenance, just pull down the data needed whenever it is needed. 

WHO ARE WE LOOKING FOR?
As a Machine Learning Engineer in the Automated Mapping Platform team, you are a highly skilled software engineer and especially a specialist in Python or C++ playing a key role building our state-of-art machine learning pipeline. You are willing to utilize your “superpower” in Deep Learning and Image Processing, and you are also enthusiastic to learn and leverage cutting edge mapping technology to build a global ecosystem for the emerging new automated mobility industry. 

 

RESPONSBILITIES

 

  • Design and develop robust machine learning pipelines in different complex scenarios
  • Design and build state-of-art machine learning algorithms in automated mapping industries from aerial/satellite imagery and probe data
  • Involved in the process of maintaining the map database used by millions users at global scale.
  • Work closely with top solution engineers in cross-functional teams to determine quality, responsibility and associated timelines
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    MINIMUM QUALIFICATIONS

     

  • Bachelor’s degree in Computer Science, Physics, Mathematics or closely related field
  • 4+ years of relevant work experience in development of product using Machine Learning/Deep Learning and Image Processing technology
  • Develop solutions for real-world Large-scale (millions of devices) problems
  • Experience specifically with machine learning framework, PyTorch or Tensorflow or Keras, with high level coding skills in C++ and/or Python
  • Proficiency in English
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    PREFERRED QUALIFICATIONS

     

  • Experience in the field of mixing remote sensing and geography
  • Experience with AWS
  • Agile/Scrum Experience and Working knowledge of typical agile tools (Git, Jenkins, Docker, JIRA, Confluence etc)
  • Experience specifically with tools for spatial analysis, gdal, QGIS
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    If you are currently located at outside of Japan, don’t worry, we’ll set an interview over Google Hangout Meet or Skype.