R&D Researcher – AI and Machine Learning

General Motors•Warren, MI

3d•Hybrid

About The Position

Identifies, defines, and formalizes problems such that they can drive design, development, and deployment of algorithmic solutions to those problems using artificial intelligence, machine learning, and other techniques at their disposal. The role uses artificial intelligence (AI) as the tool and Machine Learning (ML) is the link that helps contextualize problems and connects them back to data science (and the scientists) so that results and solutions for specific problems are attainable. GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week or other frequency dictated by their manager. Relocation benefits are available for candidates who qualify under company policy.

Requirements

Ability to identify, define, and formalize problems
Proficiency in using artificial intelligence (AI) and machine learning (ML) techniques
Understanding of data science principles
Ability to develop and deploy algorithmic solutions
Will not require GM immigration sponsorship now or in the future (including direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company like H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

Responsibilities

Identifies, defines, and formalizes problems
Drives design, development, and deployment of algorithmic solutions using artificial intelligence, machine learning, and other techniques
Uses artificial intelligence (AI) as the tool
Uses Machine Learning (ML) to contextualize problems and connect them back to data science
Ensures results and solutions for specific problems are attainable