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

jfalkowski jan.falkowski at essess.com
Tue Feb 10 08:36:45 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:

http://www.essess.com/about/careers/

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

Thanks,

Jan Falkowski
Chief Technology Officer
www.essess.com
51 Melcher Street, 7th Floor, Boston, MA 02210

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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 problems.

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 governments.

You will:

- Design and implement computer vision systems to characterize and classify
building energy issues using thermal, night-vision and LIDAR data
- 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 applications

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.



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