Senior AI/ML Engineer

1 week ago


Chennai, India GGS Information Services Full time

About the Role We are looking for a highly skilled and innovative AI/ML Engineer (Contract role) to join our Agentic AI and Generative AI (GenAI) development team. The ideal candidate will be hands-on in building and optimizing Multimodal RAG architectures, intelligent agents, and enterprise-grade GenAI automation systems . This role offers a unique opportunity to work on next-generation Agentic AI frameworks , combining LLMs, multimodal retrieval, and automation pipelines for global enterprise use cases. Key Responsibilities Design, build, and deploy Multimodal RAG architectures and LangGraph-based Agentic AI systems for enterprise automation. Develop and optimize chunking strategies, embedding pipelines , and vector database integrations (Vertex AI, PGVector, Pinecone). Integrate LLMs (Gemini 2.5, Gemma, LLaMA 4, etc.) into GenAI workflows and automation pipelines. Implement and maintain CI/CD pipelines , supporting MLOps/LLMOps frameworks for continuous delivery. Collaborate with cross-functional teams to ensure scalable deployment on GCP (Vertex AI) platforms. Continuously evaluate, monitor, and fine-tune models for precision, recall, relevance, faithfulness , and cost efficiency . Contribute to the development of evaluation frameworks (e.g., RAGAS) and AI efficacy dashboards. Required Skills & Experience Minimum 4+ years of experience in AI/ML model development with a focus on GenAI, RAG, or Agentic AI systems. Proven hands-on experience with: Vector databases: PGVector, Pinecone, or similar Multimodal data processing: text, image, audio embeddings and chunking Embedding models and vector search optimization Practical knowledge of LangChain, LangGraph , and LLMOps toolkits. Familiarity with GCP Vertex AI or equivalent ML platforms. Experience with CI/CD , MLflow , or other MLOps automation pipelines. Exposure to prompt engineering, fine-tuning , and LLM model integration . Good to Have Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science , or related disciplines. GCP/AWS/ML certifications are an advantage. Contributions to open-source AI projects or publications in GenAI / RAG / Agentic AI domains. Strong problem-solving ability and a mindset for rapid prototyping and experimentation .


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