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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 production-grade GenAI agent systems for enterprise customers, integrating Google Cloud’s AI stack with live infrastructure and driving ROI from prototypes to scalable solutions.
Build and maintain AI infrastructure, models, and tools that power Riskified’s fraud and risk platform, including RAG systems and agentic frameworks for real-time decision-making.
Build and deploy AI-powered applications and automation using LLMs (GPT, Claude, Gemini), Python, Azure, and Kubernetes while integrating security and CI/CD pipelines.
Build and deploy AI/GenAI models (NLP, LLMs, RAG) to automate workflows and improve business processes in a real-estate services company.
What You''ll Do Design, develop, and deploy enterprise-grade AI applications using modern software engineering best practices. Build and enhance agentic AI solutions, AI copilots, and intelligent workflow automation.…
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.
Own the product roadmap for an AI-powered enterprise contact center, integrating Google CCAI and generative AI to improve customer service workflows.
Designs, builds, and maintains generative AI agents and RAG pipelines, integrates AI into enterprise systems like Salesforce and MuleSoft, and establishes evaluation frameworks for agent performance.
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.
Salary: £33,000 - 60,000 per year Requirements: We are looking for strong experience in C# and .NET, including .NET Core 8/10+. We need proven experience building backend services, APIs, and microservices. We value…
Build and deploy LLM agents and RAG systems for banking workflows, fine-tuning models and orchestrating multi-agent pipelines in Python.
Senior Data Scientist builds ML/NLP models and LLM/RAG systems to extract insights from Medicaid claims and policy data, improving program oversight and health outcomes.
Build and deploy AI/ML prototypes and integrations to automate workflows for finance and shared-service teams using Python, LLMs, and cloud APIs.
Design, build, and deploy enterprise AI/ML and LLM solutions using Databricks, MLflow, and cloud platforms, covering the full AI product lifecycle.
Designs and deploys secure enterprise AI solutions on Azure for a Federal Government agency, building AI agents and RAG systems while enforcing governance and security policies.
Lead AI engineering for commerce software, designing and scaling AI agents and retrieval systems to power enterprise marketplaces and retail media.
Build and deploy production-grade AI systems, including LLMs, RAG, and AI agents, to power intelligent commerce features for Mirakl’s marketplace platform.
Designs end-to-end AI systems (agents, LLM services with RAG, memory, tool calling) and embeds them into an enterprise stack while controlling latency, cost, and stability.
Build and deploy AI-powered features like RAG pipelines and agent systems using Python/TypeScript and LLM frameworks (OpenAI, Anthropic, LangChain/LlamaIndex).
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