AI/ML Engineer

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Experience :

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About The Role

Key Responsibilities

• Design, develop, and deploy Generative AI applications using LLMs, LangChain, LangGraph, and RAG pipelines.
• Build scalable backend services and APIs using FastAPI in a microservices architecture.
• Collaborate with cross-functional teams to translate business requirements into robust AI/ML solutions.
• Own end-to-end technical delivery of AI projects, including architectural decisions, implementation, and deployment.
• Apply strong ML/NLP fundamentals to build and fine-tune models that solve real-world problems.
• Write clean, modular, and scalable Python code with a strong focus on performance and reliability.
• Mentor junior engineers and contribute to engineering best practices.
  

Required Skills & Qualifications

• 5- 8 years of experience in AI/ML engineering or software development with a focus on machine learning and backend systems.
• Strong hands-on experience with Generative AI technologies: LLMs, LangChain, LangGraph, and RAG.
• Proficiency in FastAPI and building production-ready microservices.
• Deep understanding of ML/NLP concepts, data preprocessing, and model deployment.
• Excellent Python programming skills and a solid grasp of algorithmic problem-solving.
• Proven ability to take technical ownership and clearly explain project architecture and components.
• Experience with version control (Git), CI/CD pipelines, and cloud-based development (AWS/GCP/Azure) is a plus.
  

Preferred Qualifications

• Prior experience deploying AI/ML solutions in enterprise environments.
• Familiarity with vector databases, embeddings, and model monitoring tools.
• Exposure to MLOps tools and frameworks (e.g., MLflow, Weights & Biases).