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Staff AI Research Scientist

Posted on Apr 19, 2021 by LG Corp

Santa Clara, CA 95050
Immediate Start
Annual Salary

The goal of the Advanced AI organization is to explore and develop novel AI/ML technologies and algorithms in support of LG's products and initiatives. We are looking for an AI/Machine Learning Scientist or Engineer with experience working with data and developing ML models, algorithms, and tools. You will be part of a team that designs novel experiments, evaluates existing state-of-the-art, and creates prototype implementations focused on building machine learning models for edge devices. This role also offers opportunities to work on novel research and publish high quality papers and patents. You will be based in Silicon Valley and work alongside a multi-disciplinary team that includes Data Scientists, ML/AI Scientists, and Product Managers

Principal Duties and Responsibilities:

Work with other members of the team to develop the technical roadmap for our projects and execute the full lifecycle of model development including data acquisition, data preprocessing, modeling, validation, and deployment.
Stay up-to-date on developments in machine learning, particularly for Tensorflow/Pytorch/Keras.
Become a subject matter expert on topics related to the domain you are working in and the technologies you use.
What we value:

Ability to collaborate effectively with other team members.
Willingness to grow and learn as the role demands.
The ability to work independently and take ownership.
The ability to make everyone around you better.

Required Skills:

An M.S./Ph.D. in Computer Science, Electrical Engineering, Statistics or related quantitative discipline and 2 -3 years experience post PhD.
Demonstrable experience in coding/developing/productionizing ML algorithms, solutions, and delivering/deploying prototypes.
Experience with classical ML techniques as well as deep learning.
Strong communication and interpersonal skills.

Preferred skills:

Experience building models in computer vision especially in ADAS.
Experience with at least one of the major cloud providers preferably AWS.
Peer-reviewed publications in the field of machine learning or data science.

Reference: 1171245363

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