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The Company: Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company, leveraging the latest technologies and world’s best talent to realize exciting new possibilities in mobility…
About the role The AI Engineer (LLM/Agent) will own the conversational layer that describes Purefacts’ ML model outputs to end users, develop a “Revenue Assistant” Agent from R&D through to prototype, and design…
Build and deploy AI/ML solutions—LLM/GenAI, reinforcement learning, or MLOps—to drive personalization, customer insights, and business growth from raw data to production systems.
Build and deploy deep-learning computer-vision systems using CNNs and Vision Transformers for defence and security applications.
Lead a team of ML engineers to design, deploy, and maintain AI systems for connected mobility insurance, balancing hands-on coding with technical leadership and mentorship.
Design and lead Databricks Lakehouse and Azure AI platforms, embedding GenAI, RAG, and AI agents to deliver scalable, governed data and AI solutions for enterprise clients.
Build and evaluate ML systems using AI coding agents, reviewing model-generated implementations for bugs, performance, and tradeoffs in production-ready AI/ML pipelines.
Maintain and support enterprise AI platforms, cloud-native environments, and data pipelines for a leading Hong Kong financial institution, ensuring reliability and enabling AI/ML operations.
Build and refine NLP/LLM-powered conversational AI models for a customer-service platform, focusing on production-grade RAG systems like Lyro that handle real user interactions at scale.
Hello, Greetings from Clifyx. Visa Independent Title: AI/ML Solution Architect (Generative AI & Agentic AI) Location: (Any near hub location) 12 Month Contract Minimum years of experience >15 years Job Details: Must…
Practice Manager – Cloud, DevOps & AI Practice Company: Teceze Ltd Position: Practice Manager – Digital Engineering & AI Innovation Practice Area: Cloud & DevOps, AI & Intelligent Automation,…
Основные направления работы подразделения разработки BigData Внутренняя монетизация данных (GenAI, GenOps, MLOps). Внешняя монетизация данных (OneFactor: лидогенерация, скоринг, B2G). Чем предстоит заниматься Управлять…
Департамент информационных технологий Москвы создает и развивает цифровые проекты, которые делают столицу комфортнее, а жизнь горожан — удобнее и мобильнее. Для системы управления столицей технологии — это незаменимый…
Build and lead the 0-1 AI-native data infrastructure platform from scratch, owning architecture, MLOps, and mentoring the data science team.
Lead the design and delivery of an AI-native data platform, building LLM agents, semantic search, and anomaly detection from scratch while setting technical standards for the team.
Lead AI/ML and Agentic AI projects to build predictive, prescriptive, and generative models that drive revenue growth, demand forecasting, and business decisions using Python, Azure AI, and Databricks.
Build and integrate generative-AI and ML solutions in Python to automate business processes, design LLM-based pipelines, and deploy scalable AI systems for document processing and data workflows.
Designs and operates hybrid-cloud Kubernetes platforms for Siemens Mobility’s Railigent X suite, automating infrastructure deployments and CI/CD pipelines to support scalable, secure transport solutions.
Build and run Kubernetes-based cloud infrastructure and MLOps tooling (Kubeflow, Metaflow) to train, deploy, and monitor AI models for autonomous drone systems across hybrid/multi-cloud environments.
Lead end-to-end data science projects to boost player engagement and monetization in social casino games using ML, reinforcement learning, and A/B testing.
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