高级销售工程师
Senior Sales Engineer
为什么在Nebius工作
Nebius正在引领云计算的新时代，以服务于全球人工智能经济。我们为客户创造所需的工具和资源，以解决现实世界中的挑战并推动行业发展，而无需高昂的基础设施成本或建立大型内部AI/ML团队。我们的员工与该领域最富有经验和创新精神的领导者和工程师一起，在人工智能云基础设施的最前沿工作。
我们工作的地点
总部位于阿姆斯特丹，并在纳斯达克上市，Nebius在全球范围内拥有业务，包括欧洲、北美和以色列的多个研发中心。超过800名员工中，有超过400名是具有硬件和软件工程深厚专业知识的高级工程师，以及一个内部的AI研发团队。
职位描述
我们正在为运行延迟和成本敏感型大规模工作负载的开发者原生团队构建一个高性能的人工智能推理平台。
在人工智能基础设施中，原型验证的成功并不保证生产环境的成功。这个职位确保我们所承诺的内容具备可扩展性、高效性，并与平台战略保持一致。
我们正在寻找一位高级销售工程师，成为客户的基础技术合作伙伴，并作为销售和工程团队的倍增器。你将从最初的发现到生产可行性验证，塑造复杂的AI工作负载，确保技术严谨性、经济可行性和可扩展架构决策。
你将在客户雄心、工程现实和商业增长的交汇点上运作，影响：
- 收入质量
- 工程重点
- 产品演进
- 大规模客户信任
欢迎来自欧洲的远程办公。
你的职责将包括：
战略技术探索
- 与工程团队和技术创始人进行深入的技术探索
- 理解模型需求、流量预期、延迟约束、GPU经济性以及系统依赖关系
- 将客户愿景转化为可生产的架构
- 早期识别隐藏的技术风险
商业加速
- 与销售紧密合作，参与战略性交易
- 通过架构清晰度影响交易策略
- 在工程分配前防止不一致的承诺
- 通过确保技术现实性提高PoC到生产的转化率
PoC架构与验证
- 定义可衡量的成功标准（延迟、TTFT、吞吐量、成本范围）
- 对工作负载复杂度和所需优化深度进行分类
查看英文原文
Why work at NebiusNebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.
Where we workHeadquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.
The role
We are building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale.
In AI infrastructure, PoC success does not guarantee production success. This role ensures that what we commit to is scalable, efficient, and aligned with platform strategy.
We are looking for a Senior Sales Engineer to become a foundational technical partner to our customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from first discovery through production feasibility validation, ensuring technical rigor, economic viability, and scalable architecture decisions.
You will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing:
- Revenue quality
- Engineering focus
- Product evolution
- Customer trust at scale
You’re welcome to work remotelyfrom Europe.
Your responsibilities will include:
Strategic Technical Discovery
- Lead deep technical discovery with engineering teams and technical founders
- Understand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies
- Translate customer ambition into production-feasible architectures
- Identify hidden technical risks early
Commercial Acceleration
- Partner tightly with Sales on strategic deals
- Influence deal strategy through architectural clarity
- Prevent misaligned commitments before engineering allocation
- Increase PoC-to-production conversion by ensuring technical realism
PoC Architecture & Validation
- Define measurable success criteria (latency, TTFT, throughput, cost envelope)
- Classify workload complexity and required optimization depth
- Align appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)
- Drive structured Go / No-Go decisions
- Prevent uncontrolled customization or hidden R&D
Pattern Recognition & Platform Leverage
- Identify recurring configuration patterns across customers
- Quantify demand for advanced optimizations (quantization, speculative decoding, etc.)
- Surface structured insights to Product and Engineering
- Help evolve platform capabilities based on real workload data
We expect you to have:
- Deep understanding of AI inference systems and GPU-backed infrastructure
- Experience with LLM workloads and performance-sensitive environments
- Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM).
- Ability to reason about latency, throughput, cost, and architecture tradeoffs
- Strong customer presence with engineering-first organizations
- Comfort challenging assumptions and pushing back constructively
- Commercial awareness – you understand that engineering time is a strategic resource
Preferred technical stack:
- Programming Languages– Python
- Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs
- Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent
- API and Web Frameworks– FastAPI, Flask
- MLOps and DevOps tools– Kubernetes (K8s), Docker, Git
- Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)
What success looks like:
- Strategic deals are technically sound before engineering engagement
- PoCs are clearly scoped and economically justified
- Engineering capacity is allocated predictably
- Conversion to production improves
- Customers view you as a trusted architectural advisor
What we offer
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Flexible working arrangements.
- A dynamic and collaborative work environment that values initiative and innovation.
We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!
Originally posted on Himalayas