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Lead a Data Science & AI team at Synchrony Financial, prototyping and evaluating Generative AI and Agentic AI solutions (RAG, workflow automation, agentic orchestration) across AWS/Azure/GCP while driving readiness assessments and cross-functional delivery.
Principal ML Engineer owning the end-to-end architecture of Disney's News & Entertainment ML platform, driving personalization and recommendation systems at scale across brands like ABC News, Marvel, and Disney Studios using AWS, Spark, Kafka, and deep learning.
The Technical Architect will design and implement scalable, fault-tolerant AI systems on Google Cloud, bridging the gap between research and production. The role involves leading MLOps lifecycles, defining compute strategies for AI workloads, and mentoring teams to build resilient, cloud-native architectures.
Commodity Managers work with Engineering teams to make sure Google has the supplies and equipment to put into production the innovative products coming from our Engineering teams. As a Commodity Manager, you use your…
Leads end-to-end development of custom silicon/cloud hardware products at Google, coordinating cross-functional teams across design, manufacturing, and deployment to deliver scalable AI/infrastructure solutions.
Builds and scales production-grade Generative AI and Agentic AI solutions for enterprise clients, focusing on RAG, secure agent tooling, and scalable cloud deployments.
Build and maintain scalable GCP-based data pipelines and warehouses to power real-time sports data and AI/ML workloads for a global media brand.
Build and productionize AI-powered workflows and ML models for IT management and cybersecurity products, integrating classification, recommendations, and automation into Kaseya’s platform.
Builds and deploys data models, ML pipelines, and AI-driven analytics to extract insights from complex datasets, using SQL, Python, and cloud platforms like AWS/GCP. Bridges technical and business teams by translating data into actionable strategies.
Develops and maintains Python-based automation tools, processes web data, and builds AI-driven solutions (e.g., text classification) for SEO and digital marketing analytics in Google Cloud. Focuses on data pipelines, API integrations, and reporting with BigQuery/Looker Studio.
Designs and deploys AI-driven automation solutions to streamline workflows across engineering, operations, and business teams at a fusion energy startup, leveraging LLMs, cloud infrastructure, and agentic systems.
Design and build scalable, cloud-native AI infrastructure including MLOps pipelines, multi-modal feature platforms, and production-grade model training/deployment workflows using AWS, GCP, Azure, and AliCloud.
Build and ship full stack web apps using modern JavaScript/TypeScript and backend stacks, while integrating AI features and leveraging AI coding assistants daily.
Deploys and integrates Google’s generative AI systems (e.g., Gemini, Vertex AI) into enterprise environments, resolving integration/data/state issues to ensure production-grade AI workflows. Bridges customer needs with Google Cloud’s product roadmap via field insights and best-practice collaboration.
Google AI Architect designing and implementing advanced AI/ML and GenAI solutions on Google Cloud Platform, leveraging Vertex AI, Gemini Enterprise, BigQuery, GKE, and Cloud Run with multi-agent orchestration.
Build and maintain CI/CD pipelines and cloud infrastructure for a Conversational AI platform using Azure, Kubernetes, Helm, and Terraform.
Build production-grade conversational AI agents for Google Cloud’s largest customers, turning prototypes into scalable, secure systems while optimizing performance and enterprise integrations.
Build and maintain AI-powered data pipelines for healthcare AI systems, ensuring data quality, privacy, and scalability using Python, Dagster, BigQuery, and GCP.
Senior AI & Data Scientist builds, deploys, and evaluates ML models end-to-end, from forecasting to LLM fine-tuning, while mentoring junior team members and translating technical results for clients.
Senior AI & Data Scientist who designs, builds, and deploys end-to-end ML models (forecasting, classification, LLM fine-tuning) for enterprise clients, bridging business needs with technical execution.
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