Role: AI/ML Application Developer
Job Summary:
We are seeking a highly skilled AI/ML Application Developer to design, develop, and deploy AI/ML applications leveraging Azure AI and AWS AI services. The ideal candidate will have experience in machine learning, data processing, API development, containerization, MLOps, and security implementation.
Key Responsibilities:
AI/ML Application Development
· Develop end-to-end AI/ML applications using Python, integrating Azure AI and AWS AI services.
· Implement and fine-tune machine learning models using Azure Machine Learning and Amazon SageMaker, leveraging TensorFlow and PyTo
· Build natural language processing (NLP) applications using Azure AI Language, Amazon Comprehend, and Hugging Face transformers.
· Create AI solutions using Azure OpenAI Services, Amazon Bedrock, and Azure Cognitive Services for computer vision and speech recognition.
Data Processing & Analysis
· Develop data pipelines using Azure Data Factory, AWS Glue, and PySpark.
· Implement ETL processes with Azure Synapse Analytics and AWS Glue.
· Utilize pandas, NumPy, and Databricks for data manipulation and analysis.
API Development & Microservices
· Develop RESTful APIs using Azure Functions or AWS Lambda with Flask or FastAPI.
· Create serverless AI-driven microservices on Azure Container Apps or AWS Fargate.
· Build scalable API architectures using Azure API Management or Amazon API Gateway.
Containerization
· Deploy AI/ML applications using Azure Kubernetes Service (AKS) or Amazon EKS.
· Write Dockerfiles and configure containerized AI/ML services.
MLOps Practices
· Implement model versioning and experiment tracking with Azure ML or MLflow.
· Automate testing for AI/ML models using Azure Pipelines, AWS CodePipeline, and Pytest.
· Develop monitoring strategies using Azure Monitor or Amazon CloudWatch.
Monitoring & Observability
· Implement logging and monitoring for AI applications with Azure Application Insights or AWS CloudWatch.
· Develop custom AI monitoring dashboards using Azure Dashboards or Amazon QuickSight.
Security Implementation
· Implement encryption mechanisms using Azure Key Vault or AWS Key Management Service.
· Enforce security best practices with Azure Security Center or Amazon Inspector.
Qualifications:
· Strong Python programming experience with AI/ML libraries and cloud-based AI services.
· Hands-on experience in developing production-ready AI/ML applications on Azure and AWS.
· Expertise in data processing, ETL pipelines, and Python data analysis.
· Proficiency in containerization (Docker, Kubernetes, AKS, EKS).
· Experience with serverless APIs using Azure Functions or AWS Lambda.
· Familiarity with MLOps, model deployment, and ML monitoring tools.
· Strong understanding of security best practices in cloud-based AI/ML development.
· Excellent problem-solving skills and communication.
· Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field (or equivalent experience).
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