Posted:13 hours ago|
Platform:
On-site
Part Time
Role Proficiency:
Independently interprets data and analyses results using statistical techniques
Outcomes:
Measures of Outcomes:
Outputs Expected:
Data Mining:
Reorganizing/Filtering data:
Analysis:
Create Data Models:
Create Reports:
Document:
Manage knowledge:
Status Reporting:
Code:
Code Versioning:
Quality:
Performance Management:
Skill Examples:
Knowledge Examples:
Knowledge Examples
Additional Comments:
About the Role We are looking for a skilled and forward-thinking Cloud AI/ML Engineer to design, develop, and support scalable, secure, and high-performance generative AI applications on AWS. This role will work at the intersection of cloud engineering and artificial intelligence, enabling efficient delivery of state-of-the-art AI capabilities using services like Amazon Bedrock and SageMaker. You’ll be part of a collaborative team working on cutting-edge generative AI projects, and you’ll play a key role in implementing cloud-native solutions with best practices in infrastructure automation, security, and observability. Key Responsibilities • AI/ML Integration o Leverage Amazon Bedrock for foundation models and SageMaker for custom model training and deployment. o Build and maintain generative AI applications that use AWS-native AI/ML services efficiently. • Deployment & Operations o Develop robust CI/CD pipelines for automating infrastructure deployment and AI model lifecycle management. o Implement real-time monitoring and logging using Amazon CloudWatch and other observability tools. o Ensure availability and reliability of AI systems in production environments. • Security & Compliance o Apply AWS IAM, encryption, and other best practices to protect data and models. o Ensure compliance with organizational and industry-specific data protection standards. • Collaboration & Support o Work closely with data scientists, machine learning engineers, and product owners to translate requirements into robust solutions. o Troubleshoot and resolve issues related to model performance, infrastructure, and AWS services. • Optimization & Documentation o Continuously evaluate and optimize model performance and cloud infrastructure for cost and efficiency. o Document infrastructure, deployment workflows, and best practices for team use and knowledge sharing. • Mentorship & Guidance o Share knowledge of AWS services and generative AI best practices with peers and junior engineers. Required Skills & Experience • Proficiency in AWS services, especially EC2, SageMaker, Bedrock, and IAM. • Strong programming skills in Python and experience with containerization using Docker. • Familiarity with Kubernetes for container orchestration. • Experience building and maintaining CI/CD pipelines for AI applications and MLOps • Strong understanding of data security, compliance, and monitoring tools in AWS. • Hands-on experience managing databases and data flows in cloud environments. Preferred Qualifications • AWS certifications (e.g., AWS Certified Machine Learning – Specialty, AWS DevOps Engineer). • Experience with responsible AI practices for generative models. • Exposure to cost optimization and resource scaling strategies in production AI workloads.
Aws,Python,Ai
UST Global
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