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You will own the inference serving stack and define its technical direction and measurement roadmap. You will improve latency throughput memory efficiency and serving cost while maintaining model-quality standards. You…
About the Role North Vector Dynamics is building the next-generation unmanned systems. We’re looking for an Embedded Linux Engineer to own the software that enables these systems, from the board support packages up…
Designs and optimizes deep generative models and ML pipelines for protein design, focusing on scalable training, inference, and infrastructure in a hybrid Emeryville, CA role.
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to…
Develops and deploys ML-driven autonomy for hydrogen-powered drones, focusing on perception, planning, and real-time integration with flight systems.
Company Overview Metrea delivers effects-as-a-service to national security partners across five domains and more than a dozen mission areas. These include airborne ISR, electronic warfare, secure communications, aerial…
Geometry with consequences. Deep learning on 3D CAD data where correctness translates into steel and aluminum, not pixels. The ultimate tinkerer's playground. Physical machines, shop floors, and modern cloud…
Новая локация офиса: В ноябре переезжаем в новый офис в Сколково. Сейчас работаем на Соколе - пожалуйста, учитывайте это при отклике на вакансию. Обязанности: Выстраивать ML-инфраструктуру совместно с DevOps и MLE для…
Навыки: Docker, Cuda, CI/CD, Kubernetes, LLM. Специализации: MLOps-инженер. Хотите стать частью увлекательного процесса цифровой трансформации? Блок IT в СОГАЗ активно развивается и меняет подход к созданию продуктов.…
Builds and prototypes AI integrations for Nebius’s cloud platform, shaping reference architectures and product requirements while collaborating with partner engineering teams.
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 builds and optimizes low-level GPU inference kernels and runtime components for a large-scale AI cloud platform, focusing on performance tuning and hardware integration.
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.
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.
Builds and optimizes low-level GPU kernels and runtime components for an AI inference platform, integrating new hardware and collaborating with ML teams to improve performance at scale.
Senior engineer embedded with customers to design, build, and deploy cloud infrastructure that runs physical AI workloads like simulation, training, and inference on Nebius's AI cloud platform.
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.
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