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Leads the product vision and strategy for AI-powered creative optimization in advertising, shaping how generative AI transforms creative signals into measurable business outcomes.
Develops and evaluates advanced AI algorithms for Apple’s computer vision and video understanding systems, focusing on benchmarking, failure analysis, and agentic system design to ensure robustness and safety in production environments.
Build and maintain GenAI and agentic AI platforms for clients using Azure and Databricks, integrating AI frameworks to deliver scalable solutions.
Lead AI-driven healthcare projects, coordinating between executives, technical teams, and governance to deploy generative and agentic AI solutions while managing risk and reporting on pipeline health.
Role - Senior AI Engineer Location - Alpharetta, GA Fulltime Morgan Stanely Experience: 8 Years Key Responsibilities Design, build, and deploy Python-based AI/LLM applications using FastAPI/Flask. Develop REST APIs and…
Designs and deploys AI-powered features, builds conversational flows, and improves retrieval quality for enterprise solutions.
Build and maintain AI-driven applications, write scalable code, and collaborate with teams to improve software processes and best practices.
Build agentic AI systems using frontier LLMs, document AI pipelines, and RAG for legal/contract analysis, while collaborating with stakeholders to deliver production-grade solutions.
Build and maintain AI models and pipelines that classify enterprise AI agent conversations, detect PII, and estimate ROI for customers like Vodafone and Oura.
Build and maintain the ML platform that trains, deploys, and monitors AI/ML models across Wealthsimple’s investing, crypto, and other financial products.
Design and implement AI architecture for AXA UK, focusing on GenAI, language models, and agentic systems to enhance customer products and internal operations.
Lead GenAI adoption at Citi, designing and deploying LLM-powered features (RAG, agentic workflows) in enterprise applications while setting technical standards and mentoring teams.
A self-funded training program to become an AI or Machine Learning Engineer, covering Python, ML, and cloud tools, with recruitment support to secure a UK-based role.
Build and deploy AI-powered solutions, including copilots and RAG systems, while integrating with enterprise tools like Microsoft 365 and AWS.
Build production-grade agentic AI systems that safely process financial data, designing ingestion pipelines, evaluation guardrails, and confidence scoring in Python.
Build and scale production-grade agentic AI systems using LLMs, multi-agent orchestration, and RAG pipelines across GCP, Azure, and AWS.
Lead AI Engineer designs and delivers machine learning solutions for clients, embedding AI into live operations to drive measurable impact while mentoring teams and translating complex ideas for stakeholders.
Build and maintain AI agents and automation tools using Copilot Studio and Microsoft Power Platform, integrating with SharePoint and Azure services for the UK Department of Health & Social Care.
Build and maintain AI systems that power fundamental equity research for Asian markets, including retrieval, reasoning, and workflow automation using Python and LLM technologies.
Lead a GenAI engineering team to build AI-native processes, set standards, and scale AI practices across the business while managing costs and governance.
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