Senior Machine Learning Engineer

Senior Machine Learning Engineer\n\nLocation - Kochi, Trivandrum, Bangalore\nExperience - 10 to 15 years\n\nThis is a strongly hands-on Individual Contributor role — we are specifically looking for engineers who actively design, build, deploy, and scale AI/ML systems in production environments. While candidates may currently hold Lead/Manager titles, the expectation is deep technical ownership rather than people management or task distribution responsibilities.\n\nPreferred Domain Experience\n\nWe strongly prefer candidates from:\nTravel\nHospitality\nCruise\nLogistics\n\nSecondary preference:\nRetail\nFinTech\n\n(Note: Automotive-focused AI profiles may not align well unless they have strong retail/platform AI exposure.)\n\nWhat We’re Looking For\n\n'14; Proven experience deploying AI/ML solutions into production (beyond notebooks/PoCs)\n\n'14; Strong Python and SQL skills\n\n'14; Deep MLOps exposure:\nDocker\nAPIs\nCI/CD\nModel deployment\nMonitoring\nDrift detection & retraining.\n\n'14; Cloud experience:\nAWS / Azure preferred.\nGCP acceptable\n\n'14; Strong GenAI implementation experience:\nRAG pipelines\nEmbeddings\nVector databases\nLLM applications\n\n'14; Experience with Agentic AI / Tool-integrated AI systems:\nLangChain\nLangGraph\nFunction Calling\nMCP/tools\nNL-to-SQL systems\n\nTech Stack\n\nPython | Spark | Kubernetes | Docker | MLflow | Kubeflow | SageMaker | Kafka | PyTorch | TensorFlow | RAG | LLMOps\n\nWhat You’ll Work On\n\nLarge-scale ML systems\nReal-time AI applications\nProduction-grade GenAI platforms\nRAG & LLM-powered applications\nScalable ML infrastructure\nEnterprise AI engineering initiatives\n\nIf you’re passionate about building scalable AI systems and solving real-world engineering challenges at scale, we’d love to connect.