3 months ago
Remote, Korea, SouthStaff+
Responsibilities
- Own end-to-end technical presales and solution delivery for strategic customers, including discovery, PoCs, architecture design, and production readiness.
- Advise CTOs, ML leaders, platform engineering teams, and AI infrastructure stakeholders on complex technical solutions.
- Lead ML/AI infrastructure and MLOps architectures for large-scale GPU-accelerated training and inference workloads.
- Design, validate, and document reference architectures, Infrastructure as Code solutions, and deployment patterns using Nebius AI.
- Conduct advanced PoCs, workshops, architecture reviews, and executive-level presentations.
- Partner with Sales, Product, Engineering, Support, and Marketing to communicate customer requirements and influence the product roadmap.
- Serve as the technical authority for key customer scenarios and support conferences, hackathons, webinars, case studies, and thought leadership.
- Mentor and provide technical leadership to other Solutions Architects.
Requirements
- 10+ years of experience in senior technical roles such as Solutions Architect, Systems Architect, or ML Platform Engineer, with significant customer-facing responsibilities.
- Proven end-to-end delivery of complex presales engagements, including discovery, solution design, PoCs, and production transition.
- Deep hands-on experience with large-scale ML workloads, including GPU training and inference at scale.
- Strong expertise in cloud infrastructure, MLOps, Kubernetes-based platforms, and distributed systems.
- Hands-on experience with Infrastructure as Code and configuration management using Terraform and Ansible.
- Strong Python skills and deep understanding of GPU computing stacks, including drivers, CUDA, libraries, and performance optimization.
- Exceptional communication skills for technical and executive audiences, along with a customer-centric approach.
- Fluency in Korean and English.
- Experience with HPC and ML orchestration frameworks such as Slurm and Kubeflow is preferred.
- Experience with PyTorch, TensorFlow, NVIDIA, AWS, Azure, and Google Cloud is preferred.
- Experience influencing product direction and leading or contributing to large-scale ML deployment projects across the stack is preferred.
Benefits
- Competitive compensation.
- Career growth and learning opportunities.
- Flexibility and ownership.
- Collaborative and innovative culture.
- Opportunity to work on impactful AI projects.
- International environment with talented teams.
- Remote work based in the Greater Seoul Area.
Categories
Solutions Engineering
About Nebius
Nebius builds a full-stack AI cloud offering GPU compute, storage, and tools for training and deploying ML models for startups, enterprises, and research labs. It sells consumption-based cloud infrastructure (IaaS/PaaS) and managed services tailored to generative AI workloads, including large-scale model training and inference. The company is headquartered in Amsterdam and operates as an independent provider.