ML/AI Support Co-op at Mobis North America

Plymouth, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Jun, 26

Salary

0.0

Posted On

17 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Artificial Intelligence, Data Preprocessing, Feature Extraction, Dataset Preparation, Exploratory Data Analysis, Model Training, Supervised Learning, Unsupervised Learning, Model Performance Evaluation, Python, Data Processing Libraries, Statistics, Data Cleaning, Data Visualization, Analytical Thinking

Industry

Motor Vehicle Manufacturing

Description

Description COMPANY OVERVIEW: MOBIS Technical Center of North America is the Research & Development Center for Hyundai MOBIS, a Tier 1 supplier and an affiliate under Hyundai Motor Group. MOBIS produces and supplies a wide variety of automotive components to customers including component modules (chassis, cockpit and front-end module), core systems, eco-friendly and DAS-mechatronics. MOBIS delivers the design and development of advanced engineering, autonomous driving, infotainment, component modules, safety, brake and steering systems, lamp, ICS/electronics, and software development solutions that consider the safety and convenience of our customers as well as the future. Requirements REPORTS TO: Department Manager / Team Lead FLSA CLASSIFICATION: Hourly, Non-Exempt ESSENTIAL FUNCTIONS AND SKILLS: Typical responsibilities include but are not limited to the following: • Support machine learning and AI development activities across engineering teams. • Assist with data preprocessing, feature extraction, and dataset preparation for model training. • Conduct exploratory data analysis to identify patterns, trends, and data quality issues. • Implement basic ML workflows such as supervised and unsupervised learning experiments. • Evaluate model performance using standard metrics and validation techniques. • Develop Python scripts to automate data processing and model evaluation tasks. • Collaborate with engineers and researchers to support ongoing ML/AI initiatives. • Document methodologies, experiment results, and model behavior. ADDITIONAL REQUIRED SKILLS / REQUIREMENTS: • Foundational understanding of machine learning concepts including supervised/unsupervised learning, model evaluation, and feature engineering. • Proficiency in Python and familiarity with common data processing libraries. • Experience with basic statistics, data cleaning, and visualization. • Ability to work with structured and unstructured datasets. • Strong analytical thinking and problem-solving skills. • Ability to learn quickly and adapt to new tools, frameworks, and technologies. In addition to the responsibilities mentioned above, tasks relating to the following areas will be assigned as required: • Be a team player. • Have great attention to detail. • Strong verbal and written communication skills. • Be reliable (with reliable mode of transportation). EDUCATION / CERTIFICATION / YEARS OF EXPERIENCE: • Currently pursuing a Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related field. PHYSICAL DEMANDS: • Primarily office and engineering lab environment. • May require extended periods of computer work, data review, and documentation. • Occasional onsite support at MTCA or OEM facilities as needed. EXPECTED HOURS OF WORK: • Standard business hours aligned with co-op schedule requirements and project needs. WORK ENVIRONMENT: • Office work is normally performed in a typical interior work environment which does not subject the employee to any hazardous or unpleasant elements. TRAVEL: • Occasional international travel • Frequent local travel OTHER DUTIES: Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice. CANDIDATE SPONSORSHIP: Mobis does not provide immigration related sponsorship for this role. Do not apply for this role if you will need Mobis immigration sponsorship now or in the future. This includes direct company sponsorship, entry of Mobis 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., H-1B, OPT, STEM OPT, CPT, E-2, TN, J-1, etc.) ADA DISCLAIMER: Mobis North America is committed to working with and offering reasonable accommodation to job applicants with disabilities. If you need assistance or an accommodation due to disability for any part of the employment process, please contact us at: MTCA_HR@mobis.com EEO STATEMENT: Mobis North America is an Equal Opportunity Employer. This company will provide equal opportunity to all individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Information collected regarding categories as provided by law will in no way affect the decision regarding an employment application. Mobis North America will not discharge or in any manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with Mobis North America legal duty to furnish information.

Responsibilities

The role involves supporting machine learning and AI development activities across engineering teams, including data preprocessing, feature extraction, and preparing datasets for model training. Responsibilities also include conducting exploratory data analysis, implementing basic ML workflows, and evaluating model performance using standard metrics.