Key Responsibilities :

- Design, develop, and deploy ML/NLP models and pipelines.

- Build applications leveraging Large Language Models (LLMs).

- Develop and maintain Retrieval-Augmented Generation (RAG) pipelines integrating vector search and LLMs.

- Design and implement multi-agent AI systems for complex workflows and decision-making.

- Lead end-to-end ML/NLP solution development from ideation to production (for Lead Engineers).

- Build reusable, scalable AI services and APIs using microservices and cloud-native architectures.

- Mentor and guide junior team members on AI best practices (for Lead Engineers).

Skillset :

- Strong expertise in Machine Learning (ML) and Natural Language Processing (NLP)

- Hands-on experience with Large Language Models (LLMs) and RAG pipelines

- Exposure to multi-agent AI systems

- Proficiency in Python and ML/NLP frameworks (PyTorch, TensorFlow, Hugging Face)

- Experience building scalable AI services, APIs, and microservices

- Familiarity with cloud-native AI architectures and production deployment

- Experience with containerization (Docker/Kubernetes) and cloud platforms (AWS/Azure/GCP) is a plus

We are looking for candidates who can join us immediately.