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Lead AI research and development for healthcare systems, designing advanced models and mentoring teams to publish cutting-edge work.
Build and ship LLM-powered features end-to-end, writing prompts, running experiments, and iterating with React/TypeScript front ends and Python/Node back ends.
Build and deploy ML models using Python, TensorFlow/PyTorch, and MLOps tools; integrate AI features into products and optimize performance.
Builds, fine-tunes, and deploys large language models and AI applications end-to-end, focusing on scalability, latency, and security.
Build AI-powered features like chatbots, Q&A, and contextual search using LLMs (OpenAI, Gemini, Claude) and develop agentic workflows with Python and MLOps.
Senior AI Engineer builds and deploys production-grade ML and LLM systems, turning business needs into scalable AI pipelines and models using Python and SQL.
Build and deploy LLM-powered agentic systems that autonomously perform structured tasks, integrating AI into existing software with a focus on reliability and scalability.
Build LLM-powered automation for clinical trials, extracting and mapping research data while ensuring compliance across global teams.
Build and deploy production-grade AI systems using RAG, agentic frameworks (LangGraph, AutoGen), and vector search (Azure AI Search, pgvector) with Python and cloud tools.
Build and ship AI-generated video content daily for brands, using automation pipelines and commercial creative tools to produce short-form ads and social-first creatives.
Design and build autonomous AI agents that decompose goals into actionable steps, integrate with enterprise systems, and deploy robust, observable agentic workflows with built-in failure handling.
Build autonomous AI agents and data pipelines using LangChain/LangGraph or Google Vertex AI Agent Builder to automate analytics and decision-making at scale.
Senior AI Engineer designs and deploys enterprise AI systems using TensorFlow, PyTorch, and LLM APIs, building scalable ML pipelines and computer vision/NLP solutions for fintech and healthcare clients.
Lead the design, optimization, and deployment of AI/ML models on AWS, using SageMaker, Bedrock, and vector databases to build scalable, cloud-native solutions.
Build and deploy multi-step AI agent workflows using LangChain, LlamaIndex, and platforms like Azure AI Studio Agents or AWS Bedrock Agents, integrating APIs and databases for automation.
Designs, tests, and iterates AI prompts to generate business-specific analyses and audit reports, collaborating with cross-functional teams to implement solutions.
Builds geospatial AI models and dashboards using UAV, satellite, and LiDAR data to deliver remote-sensing solutions for climate and sustainability projects.
Build and deploy AI/ML models on GCP for consumer data, CRM, loyalty, and e-commerce using Python, SQL, BigQuery, and Vertex AI.
Builds and ships AI-powered features for managing large datasets, including agent-driven data engineering workflows and AI tooling integrations.
Designs and builds data architectures and backend systems for AI in renewable energy, using Microsoft Fabric, Power BI, and REST APIs.
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