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Senior Backend Engineer architecting and scaling the Slingshot GenAI platform for the animation/VFX industry, using Python, Docker, AWS (ECS/Fargate), Infrastructure as Code, and REST APIs in a hybrid Vancouver role.
Develop and deploy GenAI solutions (LLMs, RAG, agents, copilots) in Python, integrating AI models into internal systems via APIs while ensuring production readiness and AI Act compliance.
Full Stack Developer on a 12-month contract who builds end-to-end web applications and integrates AI/GenAI capabilities (RAG, LLMs, chatbots) into enterprise solutions, using modern JS/TS frontends, Node.js/Python/Go backends, and cloud platforms, while leveraging AI-assisted coding tools daily.
Design, develop, and deploy production-grade Generative AI applications using LLMs, RAG pipelines, and agentic AI frameworks on Azure/AWS cloud platforms.
Build and deploy machine learning models and data pipelines for global clients, focusing on data engineering, model training, and MLOps with Python, PyTorch, and cloud platforms.
Build and productionize LLM-powered features: design prompts, integrate foundation models, automate evaluation/benchmarking, and monitor quality, safety, and cost for GenAI solutions.
Senior AI Engineer leads development of LLM-based language and voice technologies for healthcare, focusing on RAG, classification, and fine-tuning to enhance patient-provider interactions via conversational AI systems.
Build and deploy machine learning models for startups and life-science companies using Python, PyTorch, and TensorFlow in a fully remote, globally distributed team.
Develops backend systems for AI-driven 3D design review, focusing on geometry parsing, model analysis, and AI-assisted workflows to improve engineering quality and reduce rework cycles.
Designs user experiences for a cloud-native AI automation platform that optimizes Kubernetes and cloud infrastructure, requiring deep technical awareness and collaboration with engineers.
Builds AI-enhanced full-stack applications by designing frontends, APIs, and data services while integrating AI tools and capabilities into enterprise solutions.
The AI Application Engineer builds production-ready, user-facing AI applications and copilots for enterprise clients using Python, LLMs, RAG, and cloud infrastructure. The role involves bridging the gap between AI model development and scalable backend deployment to solve real-world business challenges.
Cloud/Infra Architect role at TCS in Calgary designing and implementing Azure and AWS cloud solutions, leading large-scale migrations, IaC deployments, and integrating GenAI capabilities into applications.
AI Engineer at IBM Client Innovation Centre Quebec (LGS) deploying and monitoring LLM/AI models into production using containers, CI/CD, and cloud AI services, while collaborating with data scientists on large-scale digital transformation projects.
Welcome to Your Next Adventure! We are looking for an Engineering Lead to own and drive Snoonu's Conversational AI and Driver Automation platform — a portfolio spanning IVR systems, multi-channel chatbots, and a…
Чем предстоит заниматься: Разработка и оптимизация RAG-систем на базе LLM (LLaMA, GPT-подобные модели) для обработки внутренних документов, отчётов и регламентов ключевых заказчиков; Реализация и тонкая настройка…
Builds and maintains custom automation tools for internal workflows using TypeScript, React/Angular/Vue, and Node.js/NestJS APIs, ensuring scalable, secure, and efficient solutions for marketing/adtech operations.
Builds and deploys advanced AI systems focusing on agentic workflows and RAG pipelines, ensuring safety, reliability, and performance through evaluation frameworks and guardrails.
This role is based in Seattle, Washington (open to considering San Francisco-based candidates) Why this role exists Teams increasingly build through prompts, coding agents, assistants, meetings, and automations — and…
Lead Data Scientist designing and deploying ML, NLP, and GenAI models (including RAG systems) using Python, cloud platforms (Azure preferred), and frameworks like TensorFlow, PyTorch, and LangChain for an executive search firm's Digital-IT team.
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