ML Engineer (Gen AI) - 5+ yrs - Coimbatore

Job Description - ML Engineer (GenAI / Agentic AI) Location: Coimbatore (Hybrid Work Model) Experience: 4+ years Payroll: Daksyam Technologies Duration: 6 Months (Extendable based on performance & project) Job Title: ML Engineer (GenAI / Agentic AI) Overview We are seeking an experienced ML Engineer with strong expertise in Generative AI, Agentic AI systems, and production-grade AI solution development . Candidates must possess a solid background in Machine Learning Engineering or Core Python Engineering, along with hands-on experience in building and deploying scalable AI applications. Mandatory Requirements Minimum 2.5 years of hands-on Generative AI experience . Remaining professional experience should be in: Machine Learning Engineering, or Core Python Engineering. Strong programming skills in Python and AI/ML ecosystem tools. Experience in designing, developing, and deploying production-grade AI solutions. Core Technical Skills Generative AI & LLMs Strong understanding of: Context windows and token limitations. Tokenization concepts. Chunking strategies and retrieval techniques. Prompt engineering and optimization. RAG (Retrieval-Augmented Generation) architectures. LLM evaluation and performance optimization Agentic AI Systems Hands-on experience in building and deploying Agentic AI solutions. Strong knowledge of: State management in multi-agent systems. Session management in agent-based architectures. Memory management strategies. Agent orchestration and workflow design. Multi-agent communication patterns. Experience with one or more of the following: LangGraph CrewAI AutoGen LangChain Other agent orchestration frameworks AI Communication Protocols Understanding and implementation experience with: MCP (Model Context Protocol) A2A (Agent-to-Agent) Protocols Tool integration and agent interoperability concepts Machine Learning & Engineering Experience with: Machine Learning model development and deployment. Model serving and inference optimization. API development using Python frameworks. Scalable AI application architecture. Monitoring, logging, and observability of AI systems. Production Engineering Experience Candidates should demonstrate experience in: Designing end-to-end AI/ML solutions. Building scalable and secure AI applications. Model deployment and lifecycle management. CI/CD pipelines for AI workloads. Performance optimization and cost management. Cloud-based AI solution deployment. Preferred Qualifications Master's degree in: Data Science Artificial Intelligence Machine Learning Computer Science Related quantitative field Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with vector databases and knowledge graphs. Education Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. Master's degree in Data Science or a relevant discipline is highly preferred. Job Description - ML Engineer (GenAI / Agentic AI) Location: Coimbatore (Hybrid Work Model) Experience: 4+ years Payroll: Daksyam Technologies Duration: 6 Months (Extendable based on performance & project) Job Title: ML Engineer (GenAI / Agentic AI) Overview We are seeking an experienced ML Engineer with strong expertise in Generative AI, Agentic AI systems, and production-grade AI solution development . Candidates must possess a solid background in Machine Learning Engineering or Core Python Engineering, along with hands-on experience in building and deploying scalable AI applications. Mandatory Requirements Minimum 2.5 years of hands-on Generative AI experience . Remaining professional experience should be in: Machine Learning Engineering, or Core Python Engineering. Strong programming skills in Python and AI/ML ecosystem tools. Experience in designing, developing, and deploying production-grade AI solutions. Core Technical Skills Generative AI & LLMs Strong understanding of: Context windows and token limitations. Tokenization concepts. Chunking strategies and retrieval techniques. Prompt engineering and optimization. RAG (Retrieval-Augmented Generation) architectures. LLM evaluation and performance optimization Agentic AI Systems Hands-on experience in building and deploying Agentic AI solutions. Strong knowledge of: State management in multi-agent systems. Session management in agent-based architectures. Memory management strategies. Agent orchestration and workflow design. Multi-agent communication patterns. Experience with one or more of the following: LangGraph CrewAI AutoGen LangChain Other agent orchestration frameworks AI Communication Protocols Understanding and implementation experience with: MCP (Model Context Protocol) A2A (Agent-to-Agent) Protocols Tool integration and agent interoperability concepts Machine Learning & Engineering Experience with: Machine Learning model development and deployment. Model serving and inference optimization. API development using Python frameworks. Scalable AI application architecture. Monitoring, logging,