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Senior ML engineer builds and maintains scalable cloud ML infrastructure, deploys LLMs with PyTorch/TensorFlow, and owns CI/CD, Kubernetes, and monitoring for production AI systems.
Build, train, and deploy ML models in Python using TensorFlow/PyTorch to solve business problems and maintain production systems.
Design and maintain scalable data pipelines and infrastructure to support AI, ML, and analytics initiatives for a global fintech trading platform.
Build and lead production AI systems for a global ecommerce platform, including LLMs, agents, and retrieval-augmented generation, spanning design, deployment, and monitoring.
Build production-grade AI features and services for a global ecommerce platform, integrating LLMs, RAG, and agent workflows using Java, Python, and cloud-native tools.
Design and implement cloud infrastructure, CI/CD pipelines, and GenAI solutions using Azure, AWS, Python, and Kubernetes.
Build and deploy generative AI solutions using RAG, prompt engineering, and frameworks like LangChain, while ensuring compliance with AI governance and GDPR.
Build, validate, and deploy real-time ML models for fraud detection, credit scoring, and risk modeling that power an AI agent platform for TradFi and DeFi institutions.
Leads AI agent design, testing, and deployment for a financial group, focusing on robust, safe workflows and LLM evaluation in Python and Azure.
Build and maintain AI-powered document parsing pipelines, OCR/VLM systems, and RAG knowledge bases on Azure to extract and structure data from PDFs, images, and videos for GenAI applications.
Build and optimize distributed data infrastructure for TikTok’s recommendation, search, and ads systems, focusing on real-time and offline storage, Lakehouse architectures, and ML feature pipelines.
Design and implement scalable data-science models (ML, optimization, simulation, generative/agentic AI) in cloud environments, then productionize them with engineering teams to drive business impact.
Deploys and scales AI applications for enterprise clients, integrating models from low-level GPU stacks to front-end interfaces using DevOps practices and cloud infrastructure.
Deploy and scale AI systems for enterprise clients, from GPU stacks to cloud infrastructure, while guiding integration and advising on Mistral’s AI tools.
Senior/Staff DevOps/SRE role at Mistral AI to deploy and scale AI products for enterprise customers, handling infrastructure, CI/CD, and cloud/on-prem setups.
Builds AI-native workflows and agent systems that integrate LLMs, memory, and tools into reliable, multi-step user tasks using Next.js, Python, and Kubernetes.
Build end-to-end product features across frontend, backend, and AI integrations, focusing on LLMs, RAG, and agentic workflows, with responsibilities including system design, deployment, and reliability.
Senior/Staff DevOps/SRE engineer at Mistral AI to deploy and scale AI products for enterprise customers, handling infrastructure, CI/CD, and cloud/on-prem setups.
Builds full-stack AI features using LLMs, RAG, and agent workflows in Next.js, Python, and Node.js, ensuring low-latency, reliable AI integrations for production systems.
Design and deploy AI-driven systems and automation workflows for cybersecurity and smart infrastructure, using Python, TensorFlow/PyTorch, and cloud services.
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