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Browse remote AWS positions at AI companies — SageMaker ML platform engineering, cloud AI infrastructure, and MLOps on AWS.
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Posted 1 month ago
Senior Software Engineer, Backend - Platform Team
Cresta
Canada (Remote); Toronto, Canada (Hybrid); United States (Remote)
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Posted 1 month ago
Senior Forward Deployed Engineer (AI Agent)
Cresta
Taiwan (Remote) · also open in 3 other locations
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Role guide
What to expect in remote AWS jobs
AWS is the most widely used cloud platform for AI companies. Remote AWS jobs in this space combine cloud engineering with ML infrastructure knowledge — SageMaker for model training and deployment, S3 and Glue for data pipelines, and Lambda or ECS for serving. Engineers who bridge cloud architecture and ML system design are consistently in demand.
What you'll work on
- Deploy and monitor ML models using SageMaker endpoints and pipelines
- Build scalable data ingestion and processing pipelines with S3 and Glue
- Design cost-efficient ML training infrastructure on EC2 GPU instances
- Create serverless AI feature APIs using Lambda and API Gateway
What companies look for
- SageMaker experience — training jobs, endpoints, and pipelines
- Strong AWS fundamentals — IAM, VPC, S3, EC2, ECS, Lambda
- Infrastructure-as-code with Terraform or CDK
Frequently asked questions
What AWS jobs are available remotely at AI companies?
Cloud engineering roles focused on ML infrastructure — SageMaker pipelines, data lake architecture on S3, and AI service integration. Many also involve ECS or EKS for container orchestration.
Do remote AWS AI jobs require SageMaker experience?
For ML-focused roles, SageMaker experience is a strong advantage. General cloud engineering roles may focus on ECS/EKS, Lambda, or data services instead. Check listings for the specific service stack.
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