Machine Learning-Gen Ai
Listed on 2026-07-01
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Engineering
AI Engineer (Applied/Software)
Machine Learning-Gen Ai/Data Statistics
An automotive manufacturing client is seeking a Machine Learning Engineer with a foundation in data, deep learning, and Generative AI. This role will focus on building and deploying advanced ML and GenAI solutions using numerical and statistical data to support next-generation manufacturing and engineering initiatives. The ideal candidate will develop proof-of-concept tools to automate and optimize core engineering tasks, such as weld schedule generation and automated weld gun selection using AI-driven methods.
Key Responsibilities- Design, develop, and deploy machine learning and deep learning models for manufacturing use cases.
- Build and optimize Generative AI solutions, including LLM-based applications.
- Develop and support agentic AI workflows for task automation and reasoning.
- Work with data analysts and engineering stakeholders to product ionize ML solutions.
- Evaluate model performance, scalability, and reliability in real-world environments.
- Contribute to end-to-end ML pipelines, from data ingestion to deployment.
Education:
A Master's or PhD in Mechanical Engineering, Industrial Engineering, or a related manufacturing-aligned discipline is required.
Experience:
A minimum of 3 years of experience in machine learning is required, including at least 1 year of hands-on data analysis work.
Technical
Skills:
Strong experience with machine learning and deep learning models is necessary. Applicants must have proven exposure to Generative AI, including LLMs, and experience working with numerical and structured data. Proficiency in Python, Databricks and ML frameworks such as PyTorch or Tensor Flow is required.
- Experience building or integrating AI agents, Vision learning, Sensors, or agentic workflows.
- Prior experience supporting manufacturing, automotive, or industrial engineering teams.
- Familiarity with model deployment, MLOps concepts, or cloud-based ML pipelines.
The compensation for this position will be based on experience. A benefits package is available to eligible employees.
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