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Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at…
КОМПАНИЯ « АЙ - ТЕКО» - ведущий российский системный интегратор и поставщик информационных технологий для корпоративных заказчиков. Активно действует на рынке IT России с 1997 года, входит в ТОП-400 крупнейших…
АЙ-ТЕКО — ведущий российский системный интегратор и поставщик IT-решений для корпоративных заказчиков. Мы реализуем проекты для крупных компаний и развиваем решения на основе современных технологий анализа данных и…
Senior Data Scientist Job requirements Experience Range: 5 - 8 years of experience, including at least 5 years of hands-on work in data science, analytics, or related fields, with recent exposure to agentic AI…
Build and maintain scalable data pipelines, ML models, and analytics for an iGaming/Web3 company using Python, cloud platforms, and AI to drive player engagement and fraud detection.
Designs and advises on scalable AI cloud solutions for enterprise customers, focusing on distributed training and inference pipelines using PyTorch, JAX and Kubernetes.
Solutions Architect at a cloud platform company, advising enterprise AI customers on deploying and scaling GPU workloads for ML training and inference using Nebius’s AI cloud services.
Build and optimize GPU infrastructure for AI workloads, profiling performance across hardware and frameworks to guide platform decisions and hardware development.
Builds and deploys AI/ML prototypes on a cloud platform, supports enterprise customers through technical onboarding, and feeds insights into product development.
Senior ML Engineer at Nebius builds and optimizes high-performance inference and fine-tuning platforms for large language models across tens of thousands of GPUs, focusing on throughput, latency, and cost-per-token.
Senior engineer builds and optimizes GPU clusters, InfiniBand networks, and KVM/QEMU virtualization for a cloud platform powering AI workloads.
Designs and advises on cloud infrastructure and MLOps solutions for AI/ML teams, leveraging GPU cloud platforms and modern frameworks to optimize training and inference workloads.
Own the product direction for Soperator, Nebius's Slurm-on-Kubernetes control plane for GPU clusters, shaping how ML engineers run and scale distributed AI workloads using cloud infrastructure and orchestration tools.
Early-career ML Solutions Architect builds and tests LLM-based applications, benchmarks models, and optimizes inference on a serverless AI platform, learning scalable AI deployment with mentorship from senior architects.
Designs and creates technical tutorials, sample code, and reference architectures to teach developers how to use Nebius' AI cloud infrastructure, including VMs, GPU clusters, and Kubernetes.
Senior ML Systems Engineer builds and maintains distributed AI training infrastructure for large-scale model training and reinforcement learning experiments using PyTorch, Megatron-LM, and DeepSpeed in Palo Alto.
Senior Applied Scientist at Nebius designs and optimizes efficient LLM/VLM inference methods, turning research into production systems using PyTorch, CUDA, and Triton.
Senior Machine Learning Engineer at Nebius in Palo Alto optimizing LLM inference systems for performance, cost, and reliability using frameworks like vLLM and PyTorch.
Designs and implements cloud infrastructure and MLOps solutions for AI teams, advising on GPU orchestration, Kubernetes, and IaC tools like Terraform.
Creates tutorials, sample code, and video demos to teach developers how to use Nebius’ AI cloud platform (VMs, GPU clusters, Kubernetes, SLURM) and explains best practices for ML infrastructure.
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