Senior AI/ML Engineer
VAYUZ Technologies
- Location
- Chennai, Tamil Nadu, India
- Job type
- Full-time
Required skills
- LangChain
- Python
- AWS
- Azure
- compliance
- Docker
- FastAPI
- Flask
- frontend
- GCP
- kernel
- Kubernetes
- microservices
- React
- TypeScript
- ONNX
About the role
VAYUZ Technologies
Website:
vayuz.com
Job details:
- Overall 10 + years of experience in IT Field.
- Minimum 5 years of hands-on experience in ML Engineering, AI Engineering, or LLM Engineering roles
- MANDATORY: At least 2 production-deployed AI/ML systems (describe in application: problem, scale, your ownership, tech stack used)
- Proven experience deploying LLM applications - RAG pipelines, AI chatbots, autonomous agents, or AI-powered workflows - to production cloud (AWS / Azure / GCP)
- Hands-on experience with at least one agentic AI framework: LangChain, LlamaIndex, AutoGen, CrewAI, or Semantic Kernel
- Strong Python proficiency; experience with FastAPI or Flask for building AI-serving microservices
- Experience integrating at least one LLM API in production: OpenAI, Anthropic, Azure OpenAI, Cohere, or Hugging Face
- Hands-on experience with vector databases (Pinecone / Weaviate / Milvus / Chroma / pgvector / FAISS) in production RAG systems
- Solid command of Docker and Kubernetes for containerized AI model deployment
- Understanding of prompt engineering, context window management, and LLM cost optimization
- Exposure to MLOps tooling: MLflow, Weights & Biases, or DVC for experiment tracking and model management
Good to Have
- Experience with multi-agent frameworks: AutoGen, CrewAI, LangGraph, or custom orchestrators
- LLM fine-tuning using LoRA, QLoRA, PEFT, SFT, RLHF, or DPO on domain-specific datasets
- Inference optimization experience: vLLM, TensorRT-LLM, ONNX, model quantization (INT4/INT8), or distillation
- GenAI observability experience with LangSmith, LangFuse, Arize AI, or Evidently AI
- Knowledge of responsible AI, AI governance, output guardrails, bias detection, and factuality validation
- Open-source contributions to GenAI, LLM, or agentic AI tooling
- Frontend exposure (React, TypeScript) for building internal AI dashboards or chat interfaces
- Familiarity with enterprise AI compliance, data privacy, and security best practices (SOC 2, GDPR)
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