Hybrid
Full-Time
Thiruvananthapuram Taluk, India
India
Skills
PyTorch
Large Language Models (LLM)
Neuro-Linguistic Programming (NLP)
LangChain
Microsoft Azure Machine Learning
TensorFlow
Microsoft Copilot Studio
Retrieval-Augmented Generation (RAG)
Microsoft Power Platform
AWS SageMaker
About the Role
We are looking for a highly experienced and innovative Senior AI/ML Engineer to design, develop, and deploy advanced AI and ML solutions. The role requires expertise in building scalable applications using Azure and AWS platforms, extensive knowledge of LLMs, NLP, vector databases, and real-time AI pipelines, and a strong ability to mentor and lead. You will collaborate with cross-functional teams to transform business requirements into AI-driven applications and ensure the reliability, scalability, and security of deployed systems.
Key Responsibilities:
• Design cloud-native AI architectures for personalized recommendations, conversational systems, and real-time analytics.
• Leverage generative AI technologies like LangChain and RAG to build advanced AI solutions.
• Train, fine-tune, and deploy ML models using Microsoft Copilot Studio, Power platform, Azure ML, AWS SageMaker, AWS bedrock
• Implement CI/CD pipelines for seamless model updates and scaling.
• Build and optimize ETL workflows for large-scale data processing using Azure Data Factory and AWS Glue.
• Integrate data pipelines with AI/ML models to enable real-time decision-making.
• Deploy robust MLOps practices, including automated monitoring and model retraining.
• Enhance AI model security through advanced techniques like LLM Guard and PromptInject.
• Collaborate with stakeholders to define AI use cases and ensure alignment with business objectives.
• Document AI workflows, data pipelines, and deployment processes for reproducibility.
Requirements:
• 5+ Years of experience in code development with Java, Python, Vscode
• Proficiency in PyTorch, TensorFlow, and deep learning frameworks.
• Experience with Azure Cognitive Services, AWS AI/ML tools, and cloud-native architectures.
• Strong understanding of containerization, orchestration, and serverless computing.
• Hands-on experience with cloud automation tools like Terraform and Kubernetes.
• Proven ability to troubleshoot complex AI/ML workflows and deliver scalable solutions.
• Strong leadership and project management skills to handle multi-disciplinary projects.
• Solid understanding of NLP, computer vision, reinforcement learning, and time series forecasting.
Key Responsibilities:
• Design cloud-native AI architectures for personalized recommendations, conversational systems, and real-time analytics.
• Leverage generative AI technologies like LangChain and RAG to build advanced AI solutions.
• Train, fine-tune, and deploy ML models using Microsoft Copilot Studio, Power platform, Azure ML, AWS SageMaker, AWS bedrock
• Implement CI/CD pipelines for seamless model updates and scaling.
• Build and optimize ETL workflows for large-scale data processing using Azure Data Factory and AWS Glue.
• Integrate data pipelines with AI/ML models to enable real-time decision-making.
• Deploy robust MLOps practices, including automated monitoring and model retraining.
• Enhance AI model security through advanced techniques like LLM Guard and PromptInject.
• Collaborate with stakeholders to define AI use cases and ensure alignment with business objectives.
• Document AI workflows, data pipelines, and deployment processes for reproducibility.
Requirements:
• 5+ Years of experience in code development with Java, Python, Vscode
• Proficiency in PyTorch, TensorFlow, and deep learning frameworks.
• Experience with Azure Cognitive Services, AWS AI/ML tools, and cloud-native architectures.
• Strong understanding of containerization, orchestration, and serverless computing.
• Hands-on experience with cloud automation tools like Terraform and Kubernetes.
• Proven ability to troubleshoot complex AI/ML workflows and deliver scalable solutions.
• Strong leadership and project management skills to handle multi-disciplinary projects.
• Solid understanding of NLP, computer vision, reinforcement learning, and time series forecasting.