Job Number:

1. Responsibilities

• Apply data science and statistical methods to solve complex engineering problems and enhance simulation, design, and manufacturing workflows.
• Develop Python-based tools for simulation automation, pre/post-processing, and reporting.
• Design and implement dashboards and data visualization tools to support decision-making.
• Implement intelligent algorithms for pattern recognition and anomaly detection.
• Design and execute DoEs for both virtual simulations and physical testing scenarios.
• Leverage LLMs, autonomous agents, and generative AI tools in engineering context.
• Support digital transformation initiatives through AI/ML integration.
• Collaborate with cross-functional teams (design, manufacturing, testing).
• Mentor junior engineers and contribute to technical presentations and knowledge sharing.
• Drive continuous improvement in engineering processes.

2. Preferred Experience

• B.Tech or master’s in mechanical engineering, data science, computer science or related field.
• Strong understanding of FEA and knowledge of comprehensive structural, thermal, dynamic, and multi-physics simulations.
• Knowledge on CAE tools like ANSYS, LS-DYNA & Altair Hyperworks, with an understanding of their application in nonlinear plastics simulations.
• Strong foundation in applied statistics, data analytics, and both supervised and unsupervised learning techniques.
• Foundation in engineering mechanics, materials science, and thermodynamics, knowledge of FEA tools (Ansys/LS-Dyna/Altair) is a strong asset.
• 5+ years of experience in data science and CAE , preferably in the automotive industry.
• Proficiency in Python and experience with ML libraries. Experience with cloud platforms (Azure, AWS) containerization (Docker) and web frameworks (Flask, Django).
• Familiarity with DevOps practices, version control systems (Git), MLOps environments (e.g Azure ML).
• Experience with data visualization tools (e.g. Matplotlib, Plotly, PyVista)
• Experience with building and scaling analytics solutions on cloud-based platforms
• Experience working with real-world sensor data, knowledge of signal processing techniques
• Knowledge of prompt engineering and deployment of GenAI agents
• Fluency in English; willingness to travel occasionally (domestic and international).

3. Competencies

• Strong analytical and problem-solving skills.
• Ability to handle complex, multidisciplinary engineering challenges.
• Innovative mindset for developing creative solutions.
• Clear communication of technical concepts to diverse audiences.
• Strong presentation and mentoring skills.

• Passion for continuous learning and technology adoption.
• Flexibility in dynamic project environments.
• Proactive in process improvement and innovation.

• Ability to bridge simulation, testing, and AI workflows
• Strong understanding of validation strategies and test-to-simulation alignment

• B.Tech or master’s in mechanical engineering, data science, computer science or related field.