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The AI Engineer will design and implement LLM orchestration patterns and build AI agents using Python or Java. The role involves integrating multi-modal models and deploying GenAI applications across AWS, Azure, and Google Cloud platforms.
Sr. GenAI Specialist Solutions Architect at AWS focused on State & Local Government and Education customers, designing GenAI architectures using Amazon Bedrock, SageMaker, and Amazon Q, leading POCs and technical deep-dives, and driving adoption of AWS AI/ML services.
The Solutions Architect at Amazon AWS advises customers on cloud migration, optimization, and innovation, focusing on AWS services like SageMaker, DynamoDB, and S3 to design scalable, secure, and cost-efficient architectures. They bridge technical and business needs, create educational content, and mentor teams while shaping AWS roadmaps based on customer feedback.
Develops and maintains data systems, ML-driven backend services, and scalable pipelines to transform nutrition data into actionable insights for Cronometer’s health/wellness app, working at the intersection of backend, data engineering, and AI.
Build and standardize ML Ops services, data pipelines, and automation in Python and Java on AWS/Databricks to support model deployment, monitoring, and AI/ML lifecycle governance at a financial services firm.
Experience developing and deploying ETL solutions on Azure cloud using ADF, Notebooks, Synapse analytics, Azure functions and other services. Experience developing and deploying ETL solutions on Azure cloud using…
Bachelor’s degree in computer science, Data Science, engineering, mathematics, information systems, or a related technical discipline 7+ years of relevant experience in data engineering roles with primary skills on…
Senior Lead Software Engineer at JPMorgan Chase designing and implementing workflow automation solutions and AI/ML pipelines on AWS, using Python, Terraform, and AI-assisted development practices within the Corporate Sector's Cloud Enablement Team.
Lead end-to-end AI/ML development for payments, building generative and agentic systems on cloud infrastructure while ensuring scalable, secure, and compliant production deployment.
The Specialist Data Scientist will deliver end-to-end analytical solutions and actionable insights for the Mass Foundation Cluster by leveraging statistical modeling, machine learning, and data visualization. The role involves collaborating with business partners to solve complex problems using tools like SQL, Python, R, and SAS.
Design, develop, deploy, and maintain AI/ML models on AWS GovCloud using SageMaker, Databricks, PySpark, and Delta Lake for federal government programs, ensuring compliance with NIST AI RMF, EO 14110, and FedRAMP standards.
Platform Architect defining cloud-native AWS architecture, building infrastructure-as-code with Pulumi and AWS CDK, and guiding engineering delivery for scalable, HIPAA-compliant healthcare technology platforms.
NOTE: This is a 1-year, Fixed-Term Position. Are you an AI/GenAI engineer who loves shipping real systems? Join Stanford’s Enterprise Technology team to design, implement, and support AI solutions across university use…
MLOps + DevOps Engineer responsible for operating an AI-native platform with agentic systems, ML workloads, and backend services on AWS. Core technologies include AWS (EKS, Lambda, Bedrock, SageMaker), Kubernetes, Kafka, Terraform, and observability stacks like Grafana, Prometheus, and OpenTelemetry.
Beacon AI is seeking Cloud and ML Infrastructure Engineers to build and maintain scalable AWS infrastructure and LLM platforms for aviation systems. The role involves designing RAG pipelines, managing model inference, and ensuring secure, high-performance deployments using tools like AWS, Python, and LangChain.
Designs and leads enterprise-scale AI/ML and Generative AI solutions, focusing on LLMs, RAG architectures, and cloud-based deployments while mentoring teams and ensuring governance.
AI/ML Engineer designing and deploying end-to-end LLM and RAG pipelines, MLOps workflows, and data integration systems on AWS (SageMaker, Bedrock, Lambda, EKS) for enterprise clients in regulated industries.
Build and scale enterprise-grade generative AI systems using Python, AWS, and frameworks like LangChain; design agentic workflows, RAG pipelines, and secure AI services for Fortune 500 clients.
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