- Design, develop, and deploy scalable AI/ML and Generative AI solutions.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using modern frameworks and vector databases.
- Develop LLM-powered applications leveraging prompt engineering, AI agents, and multi-agent workflows.
- Fine-tune, evaluate, and monitor machine learning and deep learning models.
- Build REST APIs and backend services for AI applications.
- Design data preprocessing, feature engineering, and model evaluation pipelines.
- Integrate structured and unstructured data sources to deliver contextual AI solutions.
- Collaborate with cross-functional teams including Data Engineering, DevOps, and Product teams.
- Ensure scalability, reliability, and performance of AI applications in production environments.
Programming & Development :
- Strong hands-on experience in Python and SQL.
- Experience building APIs using FastAPI or similar frameworks.
- Strong understanding of software engineering best practices and Agile methodologies.
Machine Learning & Deep Learning :
- Hands-on experience with :
- Scikit-learn
- TensorFlow
- PyTorch
- Keras
- Strong understanding of :
- Regression
- Classification
- Clustering
- Feature Engineering
- Model Evaluation
- Hyperparameter Tuning
NLP & Generative AI :
- Minimum 1 year of hands-on experience in GenAI/LLM projects.
- Experience with :
- Large Language Models (LLMs)
- Prompt Engineering
- RAG Architectures
- Agentic AI / Multi-Agent Systems
- LangChain
- LangGraph
- OpenAI APIs
- Hugging Face
- LangSmith
RAG & Vector Databases :
- Experience working with :
- Pinecone
- FAISS
- Knowledge of embedding models and semantic search architectures.
- Experience with RAG evaluation metrics such as RAGAS, BLEU, and ROUGE.
Cloud & DevOps :
- Hands-on experience with AWS services :
- EC2
- S3
- SageMaker
- Bedrock
- Experience with Docker, Git, JIRA, and CI/CD practices.
📌 Generative AI/ML Engineer (India)
🏢 Eliora Technology
📍 India
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