Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 6 Month(s)
Skills
Generative Artificial Intelligence (AI)
Collaboration
Communication
Conflict Resolution
Continuous Delivery
Amazon SageMaker
Amazon Web Services
Cloud Computing
Cloud Security
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Problem Solving
Continuous Integration
Data Science
Deep Learning
DevOps
Docker
Java
Python
Step-Functions
Terraform
Virtual Private Cloud
Job Details
Role: AWS ML Cloud Engineer
Location: Dallas, TX (Onsite)
Interview: F2F
Experience: 10+ years
Summary:
Seeking an AWS ML Cloud Engineer to design, deploy, and optimize cloud-native ML systems supporting our predictive automation platform. You will work with SageMaker, Bedrock, Step Functions, and AWS services to build secure, scalable ML pipelines and integrate generative AI models.
Key Responsibilities:
- Productionize ML pipelines using SageMaker, Step Functions, and EKS.
- Integrate foundation models via Bedrock and Anthropic APIs.
- Optimize ML frameworks for multi-tenant, multi-region workloads.
- Collaborate with Data Science, Engineering, and Security teams.
- Monitor, retrain, and manage ML models and pipelines.
Required Skills:
- AWS (SageMaker, Lambda, Step Functions, Bedrock), MLOps, CI/CD.
- Strong ML knowledge (supervised, deep learning), Python, Java.
- Cloud security (IAM, VPC, GuardDuty), DevOps (Docker, Terraform/CDK).
- Strong communication and problem-solving abilities.
Preferred:
- 10+ years software experience; 3+ years in ML/cloud roles.
- AWS ML or Solutions Architect Certification is a plus.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.