Senior ML Engineer
- Posted 4 days ago
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Job Description
Job Summary
We are looking for an experienced AI/ML Engineer with strong hands-on experience in production machine learning, MLOps, Generative AI, and RAG-based solutions. The ideal candidate should have strong Python and SQL skills and experience building, deploying, and monitoring AI/ML solutions in cloud environments.
Experience:9-15 Years
Location:Bangalore,Kochi and Thiruvananthapuram
Employment Type: Full-Time
Key Responsibilities
- Develop and deploy production-grade AI/ML models beyond notebooks and PoCs.
- Build scalable ML pipelines using Python and complex SQL.
- Implement MLOps practices including Docker, APIs, CI/CD, model deployment, monitoring, retraining, and drift monitoring.
- Work with AWS, Azure, or GCP cloud platforms.
- Design and implement RAG pipelines and enterprise GenAI solutions.
- Develop agentic AI and tool-based workflows using technologies such as LangChain, LangGraph, MCP, function calling, or NL-to-SQL.
- Collaborate with engineering and business teams to integrate AI/ML solutions into real-world applications.
- Optimize models and pipelines for scalability, reliability, and performance
More Info
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Key Skills
About Company
Skills:
Tensorflow, Opencv, MLops, Pytorch, Python, Azure ML, cloud vendor based ML Platforms, deep learning techniques, Sagemaker, large language models, kubeflow, model optimization, NLP technologies, GPT, BERT, mlflow, LLMOps, model fine-tuning
Skills:
Distributed Systems, LangChain, policy enforcement, LLMs, agent orchestration frameworks, LangGraph, ML platforms, cost controls, model adapters, embeddings pipelines, stateful workflow design, vector DBs, external APIs, RAG retrieval, observability
Skills:
containerization , Docker, Asynchronous programming, Python, Kubernetes, LLM agents, cloud platforms, vector databases, gRPC APIs, LLM evaluation frameworks, traditional ML DL models, model serving
Skills:
Csv, PowerShell, Pytest, Node.js, Json, Python, LangChain, GitHub Copilot, Azure OpenAI
Skills:
Memory Management, Python, AWS, Java, Scala, Apache Spark, Gcp, MLops, Databricks, Azure, model training, tool integrations, vector embeddings, retrieval systems, NLP techniques, semantic search, model monitoring, LLMOps, retraining strategies, drift detection, ML frameworks, feature engineering, prompt design, context orchestration