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Designs and advises on scalable AI cloud solutions for enterprise customers, focusing on distributed training and inference pipelines using PyTorch, JAX and Kubernetes.
About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through…
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.
Owns the security product vision and roadmap for a cloud AI platform, communicating compliance and security posture to customers and partners while aligning with engineering and marketing teams.
Builds and deploys AI/ML prototypes on a cloud platform, supports enterprise customers through technical onboarding, and feeds insights into product development.
Senior Applied ML Engineer builds and deploys retrieval, ranking, and indexing models for an agent-native search platform used by AI systems to access real-time information at scale.
Builds and scales backend systems for a cloud platform that deploys and manages AI workloads, using Go and Python to support high-performance inference and distributed infrastructure.
Senior Backend Engineer builds and scales cloud infrastructure services in Go, Java, and Python for a global AI cloud platform, handling databases, Kubernetes, billing, and monitoring.
Senior ML Engineer at Nebius to conduct applied AI research on reinforcement learning, agentic systems, and model training, using JAX and Python in a cloud infrastructure company.
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 building and optimizing large-scale AI inference and fine-tuning platforms for foundation models using JAX and modern hardware.
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 Site Reliability Engineer at Nebius to maintain and scale DevTools infrastructure (CI/CD, monorepos, artifact storage) while improving system reliability and user experience for an AI cloud platform.
Senior Site Reliability Engineer at Nebius, an AI cloud platform company, responsible for ensuring fault-tolerance, scale, and uninterrupted operations using cloud technologies, CI/CD, and infrastructure tools like Kubernetes and Terraform.
Senior Site Reliability Engineer responsible for ensuring the reliability and performance of compute nodes running virtual machines in a cloud AI platform, using Linux systems, virtualization (QEMU/KVM), and observability tools.
Build and maintain the reliability, observability, and performance of Nebius’s AI inference platform, ensuring seamless operation under extreme load while optimizing GPU workloads and Kubernetes clusters.
Builds and optimizes large-scale indexing and data processing pipelines for an AI-native search engine, handling tens of gigabytes per second of real-time data to support agentic AI retrieval systems.
Builds and optimizes a low-latency search engine runtime that serves AI agents in real time, using C++ or Rust and cloud infrastructure.
Senior engineer builds and operates a managed PostgreSQL service optimized for AI workloads, including vector search and migrations, using Go and PostgreSQL internals.
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