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Build and evaluate open-weight AI models for Canada’s sovereign stack: quantization evals, dataset pipelines, and inference benchmarks in a hybrid Victoria office.
Build and deploy RAG pipelines and large-scale AI systems for industrial use cases like predictive maintenance and smart factories using Python, PyTorch, and vector databases.
Builds and maintains core ML infrastructure and full-stack systems that power Wayfair’s generative visuals for home visualization, using Python, FastAPI, React, and cloud platforms.
Lead the architecture and development of large-scale RAG and NLP systems for vertical AI platforms, using PyTorch, vector databases, and probabilistic modeling to deliver predictive intelligence for high-stakes industries.
Build and deploy GenAI solutions like LLM-powered apps and RAG pipelines using Azure OpenAI and LangGraph for enterprise clients.
Design and productionize enterprise AI solutions using Snowflake Cortex AI, Python, SQL, and RAG architectures to automate decisions and build intelligent agents for Hydro One’s data platform.
Build and deploy AI-powered tools and automation to improve business workflows, integrating LLMs and ML models into existing systems.
Build and deploy AI/ML models, focusing on language technologies like NLP and dialogue systems using Python, PyTorch, and Hugging Face frameworks.
Build and deploy AI/ML models in Python for fintech use cases, using LLMs and MLOps pipelines while leveraging AI tools to accelerate development.
Build NLP pipelines with Flair/BERT/LLMs, process large datasets in PySpark/Pandas, and deploy ML models via Flask APIs and MLflow for Citi’s fintech and AI products.
Builds scalable Python backend services and full-stack apps with Django/FastAPI, integrates Generative AI models, and engineers data pipelines for enterprise clients.
Develop and deploy GenAI solutions in Python, focusing on RAG, fine-tuning, and multi-model pipelines, while benchmarking LLM performance and building scalable APIs for production use.
Build and deploy GenAI solutions in Python, integrating LLMs with RAG, fine-tuning, and multi-agent pipelines while maintaining robust APIs and benchmarking model performance.
Build and tune LLM-based AI agents and RAG systems for ERP automation and SaaS knowledge bases, using Python, PyTorch, LangChain, and cloud pipelines.
About "AI의 성능을 넘어, 실제 비즈니스 현장에서 완벽하게 작동할 수 있도록 데이터의 새로운 표준을 만듭니다." 대부분 기업이 AI 모델에 집중할 때, CUBIG은 AI가 실패하는 진짜 이유인 '데이터 상태' 에 집중합니다. CUBIG은 기업이 보유한 데이터를 AI가 잘 활용할 수 있도록 최상의 운영 가능 상태(AI-Ready)로 전환, 관리하며, 그…
Разработчик поддерживает и развивает высоконагруженную LLM-платформу на .NET, Python и React, оптимизируя инференс, PostgreSQL и GPU-инфраструктуру для обработки текста, изображений и аудио.
Build and deploy AI/ML models and LLM-based assistants for pharma-market analytics, including RAG systems and data-driven decision tools.
Lead a team to build and ship scalable generative AI applications using Google’s latest models, translating research into real-world products while mentoring engineers.
Design and sell AI-powered data solutions for customers, integrating data platforms, AI models, and agentic frameworks to enable scalable, secure AI deployments across industries.
Build and deploy enterprise Generative AI apps using LLMs, RAG pipelines, and AI agents with Python, LangChain, and vector databases.
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