Role : AI/ML Automation Engineer
Engagement: Long-term client support (automotive CAE + AI initiatives)
Location: Cary, NC / Troy, MI (Hybrid)
Level: Mid Senior (Open to strong mid-level with growth mindset)
Role Clarification
- This position is not a pure CAE Analyst role focused solely on running engineering simulations.
- This is not a traditional Data Scientist role operating independently from engineering workflows.
- Instead, this role serves as a bridge between AI/ML development and engineering automation, enabling intelligent solutions that integrate directly with engineering and CAE processes.
Role Overview
hiring an AI/ML Automation Engineer to support advanced automotive CAE (Computer-Aided Engineering) initiatives for a major OEM client. This role focuses on building AI-enabled automation, scripting, and predictive modeling solutions that integrate with existing CAE simulation workflows.
The ideal candidate is not required to be a CAE subject matter expert but must be comfortable working alongside CAE engineers, understanding their terminology, and translating engineering problems into AI-driven technical solutions.
Key Responsibilities
AI/ML & Agentic Automation Development
- Design and implement AI/ML workflows to accelerate engineering analysis and simulation tasks.
- Develop agentic AI solutions (LLM-driven assistants, prompt-based automation) to support engineering workflows.
- Apply modern GenAI tools (e.g., LLMs, prompt engineering frameworks) to automate repetitive or complex engineering tasks.
Engineering Workflow Scripting & Integration
- Build Python-based scripts and automation to integrate AI models into CAE toolchains.
- Support automation inside or alongside CAE platforms (e.g., ANSYS, HyperWorks, CATIA, or similar).
- Translate CAE requirements into executable automation, scripts, or AI workflows.
Predictive Modeling & Data Preparation
- Assist with preparing, organizing, and validating engineering datasets for ML training.
- Support development of predictive models (e.g., neural networks) for simulation acceleration or outcome prediction.
- Work with structured and semi-structured engineering data to support AI training pipelines.
Collaboration & Technical Translation
- Collaborate closely with CAE engineers and internal Actalent technical leads.
- Understand engineering problem statements and propose AI-based solutions.
- Communicate technical approaches clearly across AI and engineering stakeholders.
Required Qualifications
- Strong Python development experience.
- Hands-on experience with AI/ML concepts (traditional ML and/or modern GenAI approaches).
- Experience building automation pipelines, scripts, or tooling for technical workflows.
- Ability to understand engineering terminology and workflows (CAE exposure is a strong plus, not a requirement).
- Experience working in collaborative, R&D oriented environments.
Preferred / Nice-to-Have Skills
- Exposure to CAE tools such as ANSYS, HyperWorks, CATIA, LS-DYNA, or similar.
- Experience with agentic AI frameworks or LLM orchestration tools.
- Familiarity with Physics-informed ML, simulation data, or predictive modeling.
- Experience supporting automotive, aerospace, or mechanical engineering teams.
- Cloud experience (AWS, Azure, or Google Cloud Platform) for ML workflows.
Email- Phone Number : +1 321 7856 062
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