Sr. Embedded Engineer - Computer Vision/Machine Learning

North Syracuse, NY

Posted: 04/16/2019 Employment Type: Perm Industry: Engineering Job Number: 229139

Sr. Embedded Engineer – Computer Vision/Machine Learning

Softworld Inc.’ s Client is seeking a Sr Embedded Computer Vision / Machine Learning Engineer to work with a team of Computer Vision, Software, and Hardware Engineers on innovative embedded vision systems to meet challenging new product requirements, integrate into unique customer applications, and propose and deliver demonstrations of advanced technology initiatives.  In this role you will be given the opportunity to work at the frontier of embedded vision technology and apply it in several domains including the growing medical devices and scientific instruments fields.  This is an exceptional opportunity to influence future offering roadmaps and to make advanced capability practical for IoT and embedded systems and to grow your own expertise, mentor others, and deliver technology that makes a positive difference in people’ s lives.


Specific Responsibilities:

·         Provide technical contributions and leadership as senior individual contributor or small team leader to embedded machine vision / computer vision projects.

·         Work cross-functionally to elaborate needs, key requirements, constraints, and options to pursue

·         Work in collaboration with team to architect solutions, develop algorithms, and demonstrate working solutions in product intent, embedded systems.  Refine and optimize solutions documenting design constraints and latitudes.

·         Apply breadth of experience in machine vision systems, engineering expertise, creative problem solving, and design for six sigma to develop and demonstrate solutions that meet program QCDs (Quality, Cost, Delivery)

·         Deliver supporting analysis, models, and know how to define critical parameters and performance latitudes

·         Present solutions and results to internal and external customers.  Collect feedback and develop action plans.

·         Support team through implementation, validation, and transfer to production.

·         Mentor others in critical and emerging machine vision technologies.  Assist in recruiting new talent.  Collaborate with external partners and universities as needed.

·         Support the ongoing development of technology / product roadmaps and the execution of those strategies.



·         Masters degree with 6+ years’ experience or a PhD with 3+ years of experience in Electrical Engineering or Computer Science

·         Deep learning frameworks such as Caffe, Tensorflow, Tensorflow Lite – neural networks

·         Demonstrated experience with successful creation and delivery of computer vision products or technologies

·         Working, practical knowledge of core image processing techniques and machine learning in vision systems and especially deep learning approaches

·         An appreciation for the unique requirements of embedded systems

·         A breadth of experience spanning object detection, identification, classification, tracking, completeness checking, shape and dimensional inspection, surface inspection and pattern matching 

·         Strong communication skills to be able to collaborate and present solutions clearly

·         Strong analytical and diagnostic skills

·         Ability to work effectively in a fast-paced team environment

·         Willingness to travel and work in a global team of professionals


·         Hands-on experience delivering embedded systems

·         C, C++ and object-oriented design and analysis

·         Matlab, OpenCV, Python and/or other analysis tools

·         Board-level HW design or integration experience

·         Embedded SW design with respect to resource limitations and timing constraints

·         Experience with and the ability to write and present white papers to explain technical solutions

·         Transition of algorithms into FPGA accelerated implementations


Physical Requirements:

·         Mobility to work in a standard office setting and to use standard office equipment, including a computer.

·         Ability to use vison to read computer screen and read printed materials.

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