Automation – Engineering Applications (AI/ML)
Tasks
- Build RAG-based AI applications
- Build machine learning deep learning NLP models in Python
- Collaborate with engineering manufacturing quality and IT teams
- Create Power BI dashboards for engineering analytics and KPI monitoring
- Create design validation and rule based automation
- Deploy AI solutions using Azure AI services
- Develop APIs and integrate AI applications with engineering systems
- Develop and deploy AI ML solutions for engineering and manufacturing
- Develop document intelligence for engineering specifications and technical documents
- Develop generative AI and agentic AI applications with LLMs
- Develop reusable AI frameworks and best practices
- Integrate AI generated insights into Power BI and enterprise analytics
- Lead AI driven engineering application planning and execution
- Support simulation optimization and predictive analytics
Perks/Benefits
Skills/Tech-stack
AI Services | API Development | Azure AI | Azure AI Services | Azure DevOps | Azure Machine Learning | Azure OpenAI | CI/CD | Data Visualization | Deep learning | Docker | Document Intelligence | Generative AI | Git | LLM | Langchain | Language Processing | Llamaindex | MLOps | MLflow | Machine Learning | Natural Language | Natural Language Processing | Power BI | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | SQL | Scikit-learn | TensorFlow
Education
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