[robotics-worldwide] [jobs] Senior Computer Vision Engineer ­- 2D / 3D Image Segmentation & Machine Learning (Boston) - Essess Inc.

Jan Falkowski jan.falkowski at essess.com
Fri Jan 15 11:58:50 PST 2016

We're hiring at Essess (www.essess.com) for a Senior 2D/3D Computer 
Vision Engineer. 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



Senior Computer Vision Engineer - 2D / 3D Image Segmentation & Machine 
Learning (Boston)

Brief Description:

Essess (www.essess.com) is seeking a motivated Computer Vision and 
Machine Learning Engineer to be key part of our fast-paced product 
development team.  The Senior Computer Vision Engineer will design and 
build systems capable of identifying building, utility, and transit 
infrastructure assets from large data sets of high-resolution 2D imaging 
and 3D point cloud data.

The ideal candidate will have expertise or experience 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 the leader in thermal mobile data acquisition across the 
building, navigation, and utility infrastructure sectors.  Our 
combination of multispectral imaging and 3D sensing allows for data 
collection and analysis capabilities entirely unique within the field of 
mobile mapping.  We deploy the leading machine vision and learning 
techniques to automatically process, identify and analyze objects for 
applications across building efficiency, city and utility 
infrastructure, oil & gas assets, road network mapping, and nighttime 

Essess’ flagship Thermal Analysis Program delivers high-throughput, 
actionable, home thermal analyses without the need for on-site visits, 
thus providing a meaningful solution to reduce energy costs and address 
climate change.

You will:

- Design and implement computer vision systems to characterize and 
classify building, utility and transport infrastructure assets using 
thermal, night-vision and 3D point cloud 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:

- 5+ yr experience developing computer vision solutions for object 
recognition, segmentation, tracking using both machine learning and 
model-based approaches
- 3+ yr Python (preferred) or C++ development experience
- Masters or PhD in Computer Science, Electrical Engineering, or a 
related field
- Strong analytical and mathematical ability working in 2D/3D problem spaces
- Good interpersonal skills, oral/written communication and idea 
- Linux, scripting, and version control experience

Additional desired skills:

- OpenCV, PIL, Point Cloud Library (pcl), NumPy or similar library 
- Experience with supervised and unsupervised feature-based 
classification and regression techniques
- Experience developing and tuning CNN solutions
- 3D point cloud data algorithm development
- Robot Operating System (ROS) and/or experience with computer vision 
for robotic applications
- Experience with Amazon Web Services and Amazon Mechanical Turk
- Database programming experience
- SLAM or pose estimation algorithm experience
- GIS or mapping experience

What's in it for you?

- A great opportunity to work with a technology team 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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