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Design and deploy scalable cloud-based streaming analytics architectures for AWS customers using Kinesis, Kafka, and Flink, enabling real-time data pipelines and AI-driven insights.
Design and operate secure, high-performance cloud systems for government AI/ML workloads in air-gapped environments, using AWS services like SageMaker and Bedrock.
Build and deploy AI models, RAG pipelines, and LLM-powered systems for early-stage startups backed by a VC firm.
Build and deploy ML/optimization models for Amazon’s middle-mile logistics, including forecasting and network planning, using Python, SQL, and AWS services.
Design and deploy generative AI architectures for automotive and manufacturing customers using AWS services like Bedrock and SageMaker, advising on scalable AI solutions and driving adoption of AWS’s AI stack.
Builds scalable data-processing systems and tools for Amazon’s ecommerce platform using AWS services like Redshift, EMR, and SageMaker.
Design and deploy generative AI and agentic systems for AWS customers, leveraging LLMs, RAG, and multi-agent frameworks while creating technical content to drive adoption.
Build and operate the distributed orchestration engine for Amazon SageMaker AI’s Model Factory, running large-scale LLM training and customization workflows across thousands of GPUs and Trainium devices.
Design and advise customers on generative AI and ML solutions using AWS services like Amazon Bedrock and SageMaker, including RAG pipelines and agentic workflows.
Build and scale AI-powered data-prep systems for SageMaker, combining auto-labeling, LLM-as-judge evaluation, and human-in-the-loop workflows to deliver high-quality training data at scale.
Design and build enterprise-grade generative AI systems on AWS using Bedrock, AgentCore, and RAG pipelines, leading teams to deliver scalable LLM applications with agentic workflows.
Design and implement enterprise-grade MLOps/LLMOps pipelines on AWS SageMaker and EKS, focusing on model lifecycle management, CI/CD, monitoring, and governance for AI/ML systems.
Build and scale Autodesk’s AI-powered 3D model search infrastructure using Node.js, AWS services, and vector databases to deliver fast, cloud-native search experiences across products like Fusion and Forma.
You’ll advise enterprise customers on securing AI workloads, designing compliant architectures and implementing Cato’s AI security platform across cloud environments.
Builds and deploys ML models and AI solutions using TensorFlow, PyTorch, and cloud platforms to solve business problems and enhance products, while implementing MLOps for production monitoring.
Builds and leads a healthcare data platform that lets providers access patient records in real time, using Node.js/TypeScript backends, AWS services, and FHIR standards.
Senior full-stack engineer building and scaling a healthcare data platform that integrates with major US healthcare systems, using React, Node.js, TypeScript, and AWS services.
Leads the architecture and scaling of a healthcare data platform that ingests and processes clinical data for millions of patients, using cloud-native tools and modern data stacks.
Senior Data Engineer builds and scales healthcare data pipelines and platforms to consolidate and deliver patient records in real-time, using cloud-native tools like Spark, Snowflake, and AWS.
Build and maintain predictive models to drive life-insurance sales and policy growth using Python/R, SQL, and AWS SageMaker, then monitor performance with PowerBI.
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