Work instructions, procedures and information

Organizational interfaces

- Direct Manager

- Functional Manager
- Direct Reports
- Organizational interfaces

- Design Tools and Standardization Manager

- R&D; Performance Manager -AI
- Artificial Intelligence Department, IT Manager/team, CAE Metier, DL Metier

Competences requirements

- Knowledge / Qualifications

- Master’s degree or engineering degree in Mechanics, Physics and/or applied mathematics
- PhD thesis with application of AI methods would be a plus

- Previous Experience (If relevant)

- 3 to 5 years of experience in (automotive) industry

- Key technical competencies

- Proven experience in CAE/simulation and optimization tools.
- Solid experience with Python programming or equivalent language
- Have the mathematical knowledge on artificial intelligence / deep learning techniques
- Proven experience with explicit code for crash analysis or rheology simulation would be a plus

- Key behavioral competencies (be customer–centric, cultivate innovation, act with audacity, drive results, collaborate, drive engagement, value differences, be resilient, develop yourself)

- Good command in English
- Excellent cross-cultural adaptability
- Self-Task management & reporting
- Presentation Skills
- Ability to synthesize and formalize

Missions

- Main Missions

- Leading and supporting AI projects within the company to enhance the simulation process.
- Implementation of deep learning methods applied to Computer Aided Engineering (CAE).
- Be in close contact with the business end-users of deep learning methods, to support, identify and update their needs.




- Contribute to the creation of best practices and methodologies.
- Active monitoring of the scientific state of the art and its implementation in industry.

- KPI and/or main deliverables

- CAE Deep Learning Models
- Contribution to simulation Process Improvement Indicators
- Implementation of state-of-the-art industrial AI best practices

Activities

- 1. Data & Simulation Preparation
- Collect, clean, and prepare CAE datasets (crash, NVH, rheology, CFD…).
- Work with CAE teams to understand simulation output structures.
- Ensure data quality, traceability, and compliance with internal standards.

- 2. Model Development

- Develop deep learning models for surrogate modelling, prediction, and optimization.
- Implement model architectures adapted to CAE constraints
- Train and validate models on internal CAE datasets.
- Benchmark model performance vs. current CAE processes.
- Ensure robustness, explainability, and reproducibility.

- 3. Integration into Engineering Processes

- Deploy AI models into engineering workflows (tools, scripts, APIs, dashboards).
- Collaborate with CAE experts to define acceptance criteria.
- Automate repetitive simulation tasks using AI and Python tooling.

- 4. Industrialization & Documentation

- Package models for production (versioning, testing, monitoring).
- Write technical documentation, guidelines, and best practices.
- Contribute to internal AI standards and libraries.

- 5. Collaboration & Support

- Work closely with CAE, IT, and the central AI/Data Office.
- Support engineers in using AI models and tools.

Date: Sep 24, 2026

Location: Pune, IN

Job Requisition ID: 390618

📌 BU ENGINEERING & DEVELOPMENT PROFESSIONAL - AI ENGINEER (India)
🏢 OPmobility
📍 India