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Design and deploy generative AI models to solve real-world business problems, collaborating with teams to move solutions into production.
Design and implement generative AI solutions for enterprise customers, collaborating with teams to research cutting-edge models and optimize business outcomes using AWS tools.
Build AI models and APIs for geospatial imagery, including LLMs, computer vision, and AI agents, using Python and ArcGIS tools.
Build, test, and deploy AI/ML models; preprocess data and help fine-tune models for Translation Empire’s AI-driven applications.
Build and deploy production-grade AI/ML models using Python, TensorFlow, PyTorch, and MLOps tooling for scalable, real-world applications.
Ship production-grade LLM and automation systems that accelerate eSource-to-EDC workflows — with the validation rigor and audit traceability that clinical research demands. Pakistan Lahore About the role Nexa Trials is…
Build and deploy generative AI chatbots, predictive models, and analytics dashboards using Python, LLMs, and tools like Streamlit and Power BI.
Builds and tests AI/ML models, preprocesses data, and helps deploy AI-driven features using Python and libraries like scikit-learn.
Build and deploy LLM/NLP models using Hugging Face, LangChain, and cloud AI services; implement RAG pipelines and vector search for AI-driven chatbots and Q&A systems.
Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Design, build, and deploy AI-powered applications on Azure using Azure AI Services, Azure OpenAI, Copilot Studio, and Power Platform to create chatbots, knowledge assistants, and enterprise copilots.
Build and deploy production-grade ML models and RAG pipelines to replace rule-based systems, focusing on model quality, evaluation, and self-hosted LLM inference.
Build and fine-tune AI models using Python, TensorFlow/PyTorch, and cloud services like AWS Bedrock and Azure OpenAI to deliver industry-specific solutions.
Build full-stack web apps for healthcare workflows and integrate AI models (LLMs, RAG, agents) to automate audits, billing, and clinical decision support.
Build and deploy agentic AI systems using LLMs and reasoning architectures to improve patient outcomes in Philips' healthcare products.
Build and deploy agentic AI systems using LLMs and NLP for healthcare, focusing on RAG, chatbots, and structured information extraction to improve patient outcomes.
Build and deploy AI systems for enterprise customers, handling ML infrastructure, DevOps, and end-to-end AI solution integration across cloud and on-prem environments.
Build and lead a GenAI platform powering AI agents for healthcare, legal, tax, and compliance, using TypeScript, Python, and cloud-native tools to deploy scalable, safe systems that improve decision-making globally.
Build and scale AI-powered backend services in Node.js/TypeScript on AWS to power On Air’s streaming platform, integrating ML models and APIs for content optimization and recommendations.
Lead a team building AI-powered data and ML systems for eBay sellers, including pricing intelligence, demand recommendations, and seller analytics using Java/Kotlin, Python, Spark/Scala, and LLMs.
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