
Machine Learning Intern
The Machine Learning Intern will work on key aspects of the development cycle to help prototype, optimize, and evaluate models in Lytx’s product development pipeline. This is a great opportunity for a student who wants to gain hands-on experience in the world of machine learning and data science. Design and develop machine learning models to solve key business problems and improve client performance, retention and satisfaction. Analyze data to find trends, evaluate and compare effectiveness of the developed models, and report statistics on model performance. Assist on projects led by other team members via data processing, programming, monitoring of an applications already deployed to production, etc.
Available to work 40 hours/week for a 10 week period over the 2022 summer
Currently enrolled in an accredited university/college. Preferred
Experience with conventional machine learning techniques and coding packages (e.g. scikit-learn)
Experience with common deep learning model architectures including CNNs, RNNs, Transformers
Experience applying machine learning to image/video preferred
Sql
Tensorflow
Pytorch
Time Management Skills
Scikit- learn
Object Detection Frameworks
Process Improvement
Verbal communication
written communication
Adaptability
Problem-Solving
Results-Driven
Attention to detail and accuracy
Multi tasker
According to JobzMall, the average salary range for a Machine Learning Intern in 9785 Towne Centre Dr, San Diego, CA 92121, USA is $19.00 - $25.00 per hour. This salary range is based on a variety of factors, such as the amount of experience the intern has, the type of employer, and the location of the job. The salary range may also vary depending on the specific duties and responsibilities of the position.
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Lytx® is the world’s leading provider of video telematics, safety, and productivity solutions for commercial and public sector fleets. Its unrivaled Driver Safety Program, best-in-class DriveCam® Event Recorder, and proprietary machine vision and artificial intelligence technology are proven to help save lives and reduce risk.

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