Senior Cloud AI / ML Engineer
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Job Description
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
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