What are the responsibilities and job description for the AI/ML Engineer position at SATCON Inc?
Title: AI/ML Engineer
Location: Atlanta, GA
Duration:24 Months
Job Description
Al/ML Application Development
- Develop end-to-end Al/ML applications using Python, leveraging Azure Al services and AWS Al services for practical business use cases.
- Implement and fine-tune machine learning models using Azure Machine Learning and Amazon SageMaker, integrating frameworks like TensorFlow and PyTorch.
- Build natural language processing applications using Azure Al Language, Amazon Comprehend, and Hugging Face transformers.
- Create solutions using Azure OpenAl Service, Amazon Bedrock, Azure Cognitive Services, and AWS Al services for computer vision and speech recognition.
Data Processing and Analysis
- Develop date processing pipelines using Azure Data Factory, AWS Glue, and PySpark for large-scale data preparation.
- Implement ETL processes using Azure Synapse Analytics and AS Glue to prepare data for Al/ML workloads.
- Utilize pandas, NumPy, and Azure Databricks or Amazon EMR for data manipulation and exploratory data analysis.
- API Development and Microservices
- Design and implement RESTful APIs using Azure Functions or AWS Lambda with Python frameworks like Flask or FastAPl.
- Develop serverless Al-driven microservices using Azure Container Apps or AWS Fargate.
- Create scalable API architectures using Azure API Management or Amazon API Gateway for Al applications.
Containerization
- Containerize Al/ML applications using Docker for deployment on Azure Kubernetes Service (AKS) or Amazon Elastic Kubernetes Service (EKS).
- Write Dockerfiles and compose configurations for Al/ML services deployable on Azure Container Instances or Amazon Elastic Container Service (ECS).
MLOps Practices
- Implement model versioning and experiment tracking using Azure ML or Amazon SageMaker MLflow integrations.
- Develop strategies for model monitoring using Azure Monitor or Amazon CloudWatch.
Monitoring and Observability
- Implement logging and monitoring for Al applications using Azure Application Insights or AWS CloudWatch.
- Develop custom metrics for Al model performance monitoring using Azure Monitor or Amazon CloudWatch custom metrics.
- Create dashboards for visualizing Al application performance using Azure Dashboards or Amazon QuickSight.
Security implementation
- Implement encryption mechanisms using Azure Key Vault or AWS Key Management Service.
- Apply secure coding practices and perform security reviews using Azure Security Center or Amazon inspector.
- Implement security best practices for Al/ML workloads on Azure and AWS platforms.
Qualifications:
- Strong proficiency in Python programming with experience in Al/ML libraries and cloud-based Al services.
- Hands-on experience developing production-ready Al/ML applications on Azure and AWS.
- Expertise in data processing using cloud-native ETL services and Python data analysis libraries.
- Proficiency in containerization and orchestration using Docker, AKS, and EKS. Experience with serverless API development using Azure Functions and AWS Lambda.
- Strong understanding of MLOps practices and cloud-based ML platforms.
- Familiarity with Azure Al and AWS Al services for various Al capabilities.
- Excellent problem-solving skills and ability to translate business requirements into cloud-native Al solutions.
- Strong communication skills for cross-functional collaboration and stakeholder management.
- Bachelor's or Master's degree in Computer Science, Data Science, or related field, or equivalent practical experience.
