The selected candidate will assist engineers in the planning and development of embedded software solutions using data science, computer vision, machine learning, or neural networks and assist in the implementation of the completed designs. This is a paid internship.

Duties and Responsibilities

• Collect, annotate, analyze and interpret datasets for use in computer vision applications

• Evaluate, build reports, and provide recommendations on new models, algorithms, and datasets

• Update and improve data training pipeline from annotation to testing and evaluation

• Assist in the development and implementation of embedded software solutions

• Assist engineers with documenting application requirements and specifications

• Documentation of test results

Qualifications and Competencies

• Education: Pursuing BSCS, BSEE, BSCE

• Experience developing software using one or more of the following languages/frameworks (Python/Tensorflow/OpenCV/Pandas/Numpy/Linux)

• Experience with object detection and classification algorithms for computer vision applications

• Experience with LSTM regression algorithms preferred

• Understanding of source control concepts

Working Conditions

• The majority of the work will take place in a typical office setting (cubicle, desk, chair, computer, etc.) or in a lab/testing/development area (lab benches, test equipment, etc.)

• Occasional travel to vendor or partner facilities may be required (such as a contract manufacturing or engineering facility) but are rarely different from normal office or lab conditions other than possible safety glasses and ESD dissipative gear that may be required

Physical Requirements

Ability to lift 50lbs and to stand or sit for extended periods may occasionally be required

Physical Demands: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.