3 months ago
Remote, JapanStaff+
Responsibilities
- Own end-to-end technical presales and solution delivery for strategic customers from discovery through PoC, architecture design, and production readiness.
- Advise CTOs, Heads of ML, platform engineering leaders, and AI infrastructure teams as a trusted technical partner.
- Lead complex ML/AI infrastructure and MLOps architectures for large-scale GPU training and inference workloads.
- Design, validate, and document reference architectures, Infrastructure-as-Code solutions, and deployment patterns using Nebius AI.
- Execute advanced PoCs, workshops, architecture reviews, and executive-level presentations.
- Partner with Sales, Product, Engineering, and Support to represent customer requirements and influence product roadmap decisions.
- Act as the technical authority for key customer scenarios across product, support, and marketing teams.
- Support conferences, hackathons, webinars, customer case studies, and technical 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, ML Platform Engineer, or similar, with significant customer-facing responsibilities.
- Proven end-to-end delivery experience for 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 Terraform, Ansible, and Python.
- Deep understanding of GPU computing stacks, including drivers, CUDA, libraries, and performance optimization.
- Ability to communicate complex technical concepts effectively to technical and executive audiences.
- Customer-centric judgment balancing customer needs, technical feasibility, and product strategy.
- Fluency in Japanese and English.
- Experience with HPC and ML orchestration frameworks such as Slurm and Kubeflow is preferred.
- Experience with PyTorch and TensorFlow is preferred.
- Understanding of the cloud ML ecosystem across NVIDIA, AWS, Azure, and Google Cloud is preferred.
- Experience influencing product direction and contributing to end-to-end 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 and talented teams.
- Remote work based in the Greater Tokyo Area.
- Applicants must be authorized to work in the country of application and provide proof of employment eligibility.
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.