ML Cloud AWS Engineer
Core
Design and deploy AWS environments for machine learning training and inference, building scalable data and ML pipelines, and establishing MLOps practices to move models from prototype to production.
Role type
Senior IC ML Cloud Engineer (AWS)
Builds
Scalable, secure, and cost-efficient machine learning and generative AI solutions on AWS
Domain
Cloud Infrastructure + Machine Learning
Deliverable
production ML models
Required skills
Python, SQL, AWS SageMaker, AWS EC2, AWS IAM, AWS VPC, AWS Lambda, AWS ECR, AWS CloudWatch, Docker, Kubernetes (EKS), Terraform, CloudFormation, AWS CDK, CI/CD tools, Git, Machine Learning lifecycle management
Preferred skills
Computer vision, intelligent document processing, Amazon Bedrock, LLM fine-tuning, RAG systems, streaming and big data tools, model monitoring and explainability, GPU workloads, distributed training, inference optimization
Technologies
SageMaker, Bedrock, Airflow, Step Functions, Glue, API Gateway, OpenSearch, Kinesis, Kafka, Spark, EMR, MLflow, X-Ray, Cost Explorer
Responsibilities
Design and deploy AWS environments for ML training and inference; Build and maintain scalable data and ML pipelines; Establish MLOps practices for model versioning, registries, automated retraining, CI/CD, and monitoring; Provision infrastructure as code; Deploy models as REST APIs or serverless endpoints; Integrate foundation models and RAG architectures; Apply security and governance controls; Monitor and optimize cost, latency, and reliability; Containerize workloads and orchestrate with Kubernetes; Document architectures and mentor teammates.
