Key Responsibilities:

• Architect, develop, and optimize AI solutions using open-source models (e.g., Hugging Face, Ollama) and third-party LLM APIs.
• Design and implement advanced techniques such as RAG, GraphRAG, agent systems with orchestration/function calling, and LLM fine-tuning/prompt-tuning.
• Deploy and manage self-hosted open-source models (e.g., via vLLM, TensorRT-LLM) with scalable APIs.
• Integrate AI/ML solutions into production systems using FastAPI, Flask, or similar frameworks.
• Develop automation pipelines for data retrieval, preprocessing, and model evaluation, ensuring alignment with business needs.
• Stay ahead of AI trends (e.g., open-source LLM advancements, cost-efficient scaling) and drive strategic adoption.
• Ensure robust monitoring, testing, and documentation for system reliability and reproducibility.

Job Requirements:

Experience & Qualifications:

• Bachelor’s or master’s degree in Computer Science, AI, or a related field.
• Expertise in Python and backend frameworks like FastAPI or Flask.
• Hands-on experience with RAG architectures, agent systems (function calling/tool use), GraphRAG, or similar LLM-driven workflows.
• Ability to fine-tune LLMs (LoRA, QLoRA) and deploy open-source models (Llama 2, Mistral, etc.).
• Proficiency in LLM APIs (OpenAI, Anthropic, Groq) and vector databases (Pinecone, Qdrant, pgvector).
• Familiarity with NLP/ML frameworks (PyTorch, Transformers, LangChain, LlamaIndex) and cloud platforms (AWS, Azure, GCP).
• Strong experience in building scalable APIs and microservices for AI applications.

Apply Now!

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