Key Responsibilities

AI & LLM Systems

1. Build end-to-end RAG (Retrieval-Augmented Generation) pipelines for context-aware AI responses.
2. Implement and fine-tune vLLM for efficient inference of large language models (LLMs).
3. Collaborate with ML engineers to deploy transformer models (e.g., BERT, GPT variants) and vector databases.
4. 
   

Data & Database Architecture

1. Architect and optimize graph database systems (Neo4j) to model project knowledge networks and relationships.
2. Develop Python-based microservices for data ingestion, processing, and API integrations (FastAPI, Flask).
3. 
   

Performance & Operations

1. Monitor system performance, conduct A/B tests, and ensure low-latency responses in production.
2. Ensure scalability and efficiency of AI systems.
3. 
   

Requirements

1. Proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face Transformers).
2. Hands-on experience with graph databases, especially Neo4j (Cypher queries, graph algorithms).
3. Demonstrated work on RAG pipelines (retrieval, reranking, generation) using frameworks like LangChain or LlamaIndex.
4. Experience with vLLM or similar LLM optimization tools (quantization, distributed inference).
5. Knowledge of vector databases (e.g., FAISS, Pinecone) and embedding techniques.
6. Familiarity with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
7. 
   

Preferred Qualifications

1. Strong experience with FastAPI or Flask for building high-performance APIs.
2. Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow).
3. Contributions to open-source AI/ML projects.
4. Experience in performance tuning and A/B testing for AI systems in a production environment.
5. 
   

Soft Skills

1. Strong analytical and problem-solving skills.
2. Excellent communication and team collaboration abilities.
3. Self-motivated with the ability to work independently and as part of a team.
4. 
   

What We Offer

Competitive salary and performance-based bonuses.

Flexible working hours with remote work options.

Opportunities for professional development and skill enhancement.

Collaborative and inclusive work environment.

Paid sick time

Paid time off

Provident Fund

Performance bonus

Yearly bonus

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