AI / Machine Learning Model Development Engineer
Mobis North American LLC - Plymouth
First seen here today.
Opens the original listing in a new tab.
Full 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 system, 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.
Role Overview
We are seeking a motivated AI/Machine Learning Model Development Engineer to join our team and support ongoing research and engineering projects. In this role, you will collaborate closely with engineers and researchers to train machine learning models, evaluate their performance, and deploy them on embedded systems.
KEY RESPONSIBILITIES (To perform within this position successfully, the incumbent must be able to perform each essential duty satisfactorily. Other duties may be assigned.)
- Support the development of machine learning models by collecting, preprocessing, and analyzing datasets.
- Train, validate, and fine-tune ML models under the guidance of engineers and researchers.
- Evaluate model performance using appropriate metrics and testing methodologies.
- Assist in optimizing models for deployment on embedded or resource-constrained systems.
- Implement model inference pipelines and help integrate ML models into production environments.
- Stay updated on current ML techniques, tools, and frameworks relevant to the project.
AUTHORITY & SCOPE
This role operates within defined corporate policies and procedures and exercises judgment appropriate to its level of responsibility. The position may influence decisions related to functional operations, processes, or recommendations and escalate matters as required.
Qualifications (The requirements listed below are representative of the knowledge, skills, and/or ability required and preferred for this position.)
Required Education & Experience:
- Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or related fields.
- Foundational understanding of machine learning concepts such as 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.
- Hands-on experience with ML frameworks such as PyTorch, TensorFlow, and Keras.
Required Knowledge, Skills, & Abilities:
- Foundational understanding of machine learning concepts, including supervised and unsupervised learning techniques.
- Knowledge of model evaluation methodologies and feature engineering practices.
- Proficiency in Python programming and common data processing libraries.
- Strong analytical thinking and problem-solving skills.
- Excellent communication and technical documentation skills.
- Ability to collaborate effectively with engineers and researchers in a team environment.
- Ability to learn and adapt to new technologies, tools, and methodologies.
Preferred Education & Experience:
- Experience working with Jenkins for CI/CD pipelines.
- Experience working with Hugging Face transformers and LLM models.
- Exposure to embedded systems, edge AI, or model deployment technologies such as TensorRT, ONNX, or TensorFlow Lite (TFLite).
- Experience working with sensor data, driving simulators, or automotive datasets.
- Experience using Git or other version-control platforms.
- Understanding of data pipelines, automation, or experimental design.
Certificates, Licenses, and Registrations:
- None required.
PHYSICAL DEMANDS:
Position requires occasional or frequent moderate physical activity.
EXPECTED HOURS OF WORK:
- A typical work week is 45 hours/week.
- Working hours for employees are flexible with a typical day starting 7am-9am M-F.
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.
- Stress may occur periodically.
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, 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@gmobis.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 compensation information to individuals who do not otherwise have access 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's legal duty to furnish information.
Highlighted terms are keywords extracted from this posting.