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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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Posted 1 month ago
Security Engineer, Offensive Security
Anthropic
Remote-Friendly, United States; San Francisco, CA | Seattle, WA | New York City, NY | Washington, DC
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society...
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Posted 1 month ago
Forward Deployed Engineer, Infrastructure Specialist (Middle East)
Cohere
Middle East
Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Posted 1 month ago
Solutions Architect - Digital Native Business (Healthtech)
Databricks
Remote - California; San Francisco, California
As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and se...
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Posted 1 month ago
Security Engineer, Corporate Security
Notion
Dublin, Ireland · also open in 1 other location
Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and...
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Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, R...
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Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writ...
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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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Founded in 2018, Abridge is the first AI-native clinician intelligence platform organized around the patient, built for clinicians, and designed to he...
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Perplexity is looking for a Backend/Infrastructure Engineer Intern to support our small, high-impact team building the systems that power our search e...
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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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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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