[robotics-worldwide] [jobs] Computer Vision Engineer ?- 2D / 3D Image Segmentation (Boston / Remote) - Essess Inc.

Schaal Stefan sschaal at usc.edu
Mon Feb 9 08:21:25 PST 2015

We're hiring at Essess (www.essess.com) for experienced 2D/3D data
processing engineers. Our tech-stack utilizes a number of integrated
robotic sensor technologies and software tools, and we've got some
very experienced roboticists leading our technical team. Please take a
look at the job posting below as well or on our website:


Inquiries should be sent to [jobs at essess dot com]


Jan Falkowski
Chief Technology Officer
51 Melcher Street, 7th Floor, Boston, MA 02210

Computer Vision Engineer ­- 2D / 3D Image Segmentation (Boston / Remote)

Brief Description:

Essess (www.essess.com) is seeking a motivated Computer Vision and 3D
Data Engineer to be key part of our fast-paced product development
team to help create cutting-edge energy loss detection and diagnostics
products for home and building properties. The Computer Vision
Engineer will build systems capable of identifying buildings and
building components from large data sets of high resolution and
high-throughput 2D imaging and 3D point cloud data utilizing
segmentation and machine learning techniques.

The ideal candidate will have experience or expertise in 2D image
processing and computer vision, 3D point cloud data, machine learning,
and will bring an analytical approach to solving complex real world

Full Description:

Essess is all about leveraging cutting edge technology to enable
energy efficiency. Our goal is to limit energy consumption by
identifying hot spots in building infrastructures. Our customized
multi-sensor hardware captures large volumes of data for millions of
buildings and through the use of robotics, computer vision, and big
data analysis, turns the captured data into a meaningful solution to
address climate change. Essess provides a high-throughput thermal
analysis of a building’s envelope without the need for an on-site
visit. Our clients include utility companies and federal and state

You will:

- Design and implement computer vision systems to characterize and
classify building energy issues using thermal, night-vision and LIDAR
- Characterize algorithm performance with real-world data gathered
from field trials
- Support production deployment of computer vision algorithms over
city-scale data sets
- Take ownership for whole components of product development
- Work with a small team in a fast-paced environment focused on the
development and productization of algorithms for real-world

Job requirements:
- 2+ yr experience applying computer vision methods to complex problems
- Strong analytical and mathematical ability working in 2D/3D problem spaces
- 3+ yr Python (preferred), or C++ development experience
- Bachelors or Masters in Computer Science, Electrical Engineering, or
a related field
- Good interpersonal skills, oral/written communication and idea presentation
- Linux, scripting, and version control experience

Additional desired skills:
- Experience with computer vision: object recognition, segmentation,
and tracking
- OpenCV, PIL, Point Cloud Library (pcl), NumPy or similar library experience
- Robot Operating System (ROS) and/or experience with vision/3D
analysis in robotic applications
- Experience developing algorithms applied to LIDAR data
- Experience developing with Amazon Web Services and Amazon Mechanical Turk
- MongoDB or other NoSQL databases
- SLAM (simultaneous localization and mapping) or pose estimation
algorithm experience
- GIS (geographic information systems) or mapping experience

What's in it for you?
- A great opportunity to work with a technology team that is defining
new markets in the growing domain of energy optimization
- Tremendous growth opportunity; competitive compensation package
including base salary, stock and benefits

Please send your resume to [jobs at essess.com]. If you have a code
repository or portfolio of your work, please include the link in your
submission. No recruiters please.

More information about the robotics-worldwide mailing list