Tech Stack
AWSAzureCloudGoogle Cloud PlatformPythonPyTorchTensorflow
About the role
- Build and deploy semantic search pipelines, RAG systems, and conversational AI solutions.
- Design and integrate multi-agent workflows for automation and intelligent decision-making.
- Fine-tune and optimize LLMs and NLP models for domain-specific use cases.
- Deliver end-to-end AI applications: data ingestion → model training → production deployment.
- Stay current with GenAI advancements and apply them to solve real-world business problems.
Requirements
- Proven experience with LLMs and NLP/NLU techniques.
- Hands-on expertise in semantic search and RAG implementation.
- Familiarity with multi-agent frameworks (LangChain, LlamaIndex, etc.).
- Strong in Python, ML frameworks (PyTorch, TensorFlow), and vector databases.
- Exposure to cloud platforms (AWS, Azure, GCP) & MLOps best practices.
- Bachelor’s or Master’s in Computer Science, AI, Data Science, or a related field.
- Minimum 2 years’ experience in AI/ML solution development.
- Solid foundation in software engineering principles and best practices.