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Build production-grade AI agents and LLM-powered features like chatbots and RAG systems using Python, FastAPI, and third-party models (OpenAI, Gemini, Claude).
Staff engineer leading the architecture of Faire’s retailer-facing search, ranking, and Gen-AI features, building high-scale, low-latency systems with Kotlin/Java and Elasticsearch.
Build full-stack web apps and AI-powered tools using React, Python, and LangChain/LangGraph, integrating RAG workflows and LLM APIs in a regulated bank’s analytics team.
Architect and scale high-performance ad-serving infrastructure for premium formats like video and brand creatives, using Kotlin/Java, Elasticsearch, and AWS.
Builds and scales data pipelines, crawlers, and semantic search systems using Golang/Node.js, MongoDB, PostgreSQL, and vector databases to power AI-driven financial analytics and RAG workflows.
Build and scale data pipelines, crawlers, and semantic search systems using Golang/Node.js, PostgreSQL, and vector databases to power AI-driven financial analytics and RAG integrations.
Build and maintain LLM servers (Llama, Mistral, GPT API) and deploy AI agents that automate tasks like reminders, reports, and paperwork using vector databases and RAG pipelines.
Mô tả công việc: Key Responsibilities Data Engineering Pipelines Build and maintain data pipelines for Amazon SP-API, Advertising API, and other e-commerce platforms. Collect and process product reviews, sales,…
Builds Flask web apps and Plotly Dash dashboards for banking analytics, integrates local LLMs and RAG pipelines, and automates risk/compliance workflows.
Build and deploy generative AI agents, RAG systems, and ML models end-to-end using Python, LangChain, and Azure OpenAI to drive healthcare analytics and business impact.
Build and maintain data pipelines, clean and structure financial data, and integrate GenAI solutions like LLMs and RAG for a banking-focused project using Python, SQL, and ETL/ELT.
Build and maintain scalable Python-based backend services using FastAPI, Docker, and cloud platforms (Azure/AWS) for a cybersecurity-focused AI project.
Build and maintain Python-based APIs and backend services for an AI company, using FastAPI/Django/Flask, async programming, and cloud tools like AWS/Azure.
Build LLM-powered automations, chat/voice assistants, and RAG pipelines using Python, FastAPI, and vector databases; deploy cloud-native services with CI/CD and guardrails.
Build and deploy RAG pipelines and large-scale AI systems for industrial use cases like predictive maintenance and smart factories using Python, PyTorch, and vector databases.
Build and scale AI/ML pipelines and GenAI systems for GE HealthCare, automating model deployment, monitoring, and lifecycle management across hybrid/multi-cloud (AWS, Azure).
Lead the architecture and development of large-scale RAG and NLP systems for vertical AI platforms, using PyTorch, vector databases, and probabilistic modeling to deliver predictive intelligence for high-stakes industries.
Build and optimize LLM-powered backend systems for scalable AI-driven search and agentic workflows, focusing on retrieval pipelines, orchestration, and evaluation.
Build and scale face-recognition systems using PyTorch/TensorFlow, own end-to-end ML pipelines on AWS, and lead fairness analysis for biometric models in production.
Build and deploy AI/ML pipelines using Python, FastAPI, and cloud services like GCP to serve vector-based models and microservices.
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