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Jr ML Cloud AWS Engineer

EStaffLLC

Job Location:

Austin, TX - USA

Monthly Salary: Not provided by the employer

Posted: 6 October 2026 (Yesterday)

Application Deadline: 3 January 2027

Vacancies: 1 Vacancy

Job Summary

We are seeking an ML Cloud AWS Engineer for an Onsite Contract assignment with our Austin Texas client to design build and operate the cloud infrastructure and pipelines that take machine learning models from prototype to production on AWS. You will work with data scientists software engineers and security teams to deliver scalable secure and cost-efficient ML and generative AI solutions.

Key Responsibilities

* Design and deploy ML training and inference environments on AWS using SageMaker Bedrock and related services.

* Build and maintain scalable data and ML pipelines (SageMaker Pipelines Step Functions Airflow/MWAA Glue).

* Implement MLOps practices: model versioning registries automated retraining CI/CD and monitoring for drift and performance.

* Provision infrastructure as code using Terraform CloudFormation or AWS CDK.

* Deploy models as REST APIs or serverless endpoints (API Gateway Lambda ECS/EKS SageMaker endpoints).

* Integrate foundation models and RAG architectures using Bedrock OpenSearch and vector databases.

* Enforce security and governance: IAM least-privilege VPC design encryption secrets management audit logging.

* Monitor and optimize cost latency and reliability (CloudWatch X-Ray Cost Explorer).

* Containerize workloads with Docker and orchestrate with Kubernetes (EKS).

* Document architectures and mentor teammates on cloud and MLOps best practices.

Requirements

* Bachelors degree in Computer Science Engineering Data Science or a related field (or equivalent experience).

* 3 years of experience in cloud engineering ML engineering or DevOps with 2 years hands-on in AWS.

* Strong Python and SQL skills.

* Hands-on experience with SageMaker and core AWS services (S3 EC2 IAM VPC Lambda ECR CloudWatch).

* Experience with Docker and Kubernetes (EKS preferred).

* Experience with infrastructure as code (Terraform CloudFormation or CDK).

* Experience with CI/CD tools (GitHub Actions GitLab CI CodePipeline) and Git.

* Understanding of the ML lifecycle: training evaluation deployment and monitoring.

Preferred

* AWS certifications (Machine Learning Specialty Solutions Architect or DevOps Engineer).

* Experience with computer vision and intelligent document processing on AWS (Rekognition Textract).

* Experience with Amazon Bedrock generative AI LLM fine-tuning or RAG systems.

* Experience with streaming and big data tools (Kinesis Kafka Spark EMR).

* Familiarity with model monitoring and explainability tools (SageMaker Model Monitor Clarify MLflow).

* Experience in regulated or public-sector environments (FedRAMP GovCloud compliance frameworks).

* Knowledge of GPU workloads distributed training and inference optimization.

Required Experience:

Junior IC

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About Company

EStaffLLC

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