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Build and maintain the Kubernetes-based infrastructure and MLOps tooling that trains, deploys, and monitors AI models for robotic-assisted surgery at scale.
Build and deploy large-scale machine learning models and AI agents to optimize Micron’s semiconductor manufacturing workflows using distributed training and GPU optimization techniques.
Build and run production-grade LLM systems: deploy self-hosted models, set up GPU-aware inference, CI/CD, monitoring, and evaluation for AI-powered services.
Pre-sales role designing and evangelizing Kubernetes-based AI infrastructure for enterprises, focusing on Mirantis k0rdent and AI/ML deployment pipelines.
Build AI-driven automation for software engineering at a global bank: design deterministic agents, integrate LLMs into CI/CD, and deploy scalable cloud-native systems using AWS/GCP.
Build and productionize generative AI models and LLM-driven applications using PyTorch, RAG pipelines, and vector databases, while engineering robust MLOps and data pipelines in Python.
Build and deploy data products for ag-tech e-commerce and supply chain using Python, SQL, Kubeflow, and Google Cloud, specializing in recommenders, search, or operations.
Principal Staff Engineer builds and optimizes exabyte-scale data platforms for LLMs, RAG, and agentic AI systems that power CrowdStrike’s AI-native cybersecurity products.
La data et le Machine Learning sont aujourd’hui au cœur des stratégies de transformation des entreprises. Nous les mobilisons comme de véritables accélérateurs de performance, en industrialisant les cas d’usage IA de…
Lead the design and operation of AWS-based Kubernetes infrastructure for AI/ML workloads, enabling data scientists to train and deploy models at scale.
Build and operate scalable ML inference platforms for an AI-native cloud startup, designing GPU-powered serving systems, deployment pipelines, and observability for real-time AI applications.
Build and operate scalable ML inference platforms using vLLM/TGI/Triton to serve AI models with low latency and high GPU efficiency for a next-gen cloud startup.
Build and deploy enterprise LLM applications, RAG systems, and AI agents using open-source models (DeepSeek, Qwen, Kimi) and frameworks like LangChain and vLLM.
Lead a team to build and manage a centralized AI/ML Models-as-a-Service platform, overseeing model development, deployment, and MLOps pipelines for enterprise use.
Build and maintain ML engineering platforms and pipelines, deploy models to cloud instances, and collaborate with data scientists to optimize workflows using tools like Kubeflow, MLFlow, and Kubernetes.
Builds and maintains robust LLM-based AI agents and RAG pipelines, designs multi-step reasoning workflows, and implements quality evaluation frameworks to ensure reliable, production-grade AI systems.
Salary: $150 – $170 per hour About the Role The Domain Architect - AI Compute acts as the primary technical authority for the physical and logical lifecycle of high-performance GPU compute fleets across diverse client…
Build and maintain the Kubernetes-based infrastructure and MLOps tooling that trains, validates, and deploys AI models for Intuitive Surgical’s medical devices, ensuring reproducible workflows and GPU cluster health.
Solution Architect designs enterprise-scale GenAI/LLM systems, including RAG pipelines, agent orchestration, and secure on-prem deployments, while guiding clients through AI transformation and regulatory compliance.
Build and deploy ML models for credit scoring and risk assessment in a fast-growing fintech payments company, using Python, MLOps, and production-grade pipelines.
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