AI/ML Cloud Engineer

Total Experience: 6-8 years

Azure:

• Collaborate with data scientists, data engineers, developers, and business stakeholders

• Design and implement AI/ML solutions using Azure AI services such as:

o Azure OpenAI

o Azure Machine Learning

o Azure Cognitive Services (Vision, Language, Speech, Decision)

• Develop and deploy ML models using Python, R, or .NET

• Build end-to-end ML pipelines including data ingestion, training, evaluation, deployment, and monitoring

• Architect cloud-native AI solutions leveraging:

o Azure ML Workspaces

o Azure Functions

o Azure App Services

• Ensure scalability, resiliency, performance, and cost optimization

• Implement Azure security best practices:

o Managed identities

o Key Vault

o Role-Based Access Control (RBAC)

• Support production issues and continuous improvement initiatives

• Understanding on Cosmos DB

• AWS: Design and implement ML pipelines using AWS SageMaker, including data preprocessing, model training, tuning, and deployment.

• Develop and integrate Generative AI applications using AWS Bedrock and foundation models (e.g., Titan, Claude, Llama).

• Build APIs and microservices to expose ML models for consumption by applications.

• Optimize ML workflows for cost efficiency and scalability in AWS environments.

• Collaborate with data scientists and business stakeholders to translate requirements into technical solutions.

• Implement security best practices for ML models and data in AWS.

• Monitor and maintain deployed models, ensuring performance and reliability.

• Hands-on experience with AWS SageMaker (training, inference, pipelines, model registry).

• Strong knowledge of AWS Bedrock and generative AI concepts (LLMs, prompt engineering).

• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).

• Experience with AWS services: Lambda, API Gateway, S3, IAM, CloudWatch.

• Familiarity with MLOps practices and CI/CD pipelines for ML.

• Understanding of data engineering concepts and feature engineering.

• Excellent problem-solving and communication skills.

• Azure: Strong experience with Microsoft Azure

• Expertise in Azure AI / ML services

• Proficiency in Python (TensorFlow, PyTorch, Scikit-learn preferred)

• Hands-on experience with REST APIs and microservices

• Knowledge of SQL and NoSQL data stores (Azure SQL, Cosmos DB)

• Azure AI Engineer Associate Certified (AI-102)

• AWS: AWS Bedrock, SageMaker, Machine Learning, Python etc

Desired Skill Sets:

Networking & Connectivity

• Design and manage Azure networking components:

o Virtual Networks (VNet), Subnets

o Network Security Groups (NSG)

o Azure Load Balancer, Application Gateway, Azure Front Door

• Troubleshoot network performance and connectivity issues

Security, Identity & Compliance

Collaboration & Support

• Work closely with application teams, security teams, and architects

• Provide L2/L3 production support for Azure environments

• Participate in architecture reviews and cloud migration initiatives

• Document architecture, procedures, and operational runbooks"