AI/ML Specialist Solutions Architect

About this role

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 to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

Customer Experience:

The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The Role

Nebius is seeking an experienced AI/ML Specialist Solutions Architect to partner with AI-first customers building and operating large-scale machine learning and generative AI workloads. In this role, you'll serve as a trusted technical advisor, helping customers design, optimize, and productionize distributed training and inference environments running across hundreds to thousands of GPUs. This is a highly technical, customer-facing role for someone who has hands-on experience with modern LLM training, inference, and AI infrastructure at scale - not just proof-of-concepts, but production deployments.

You are welcome to work remotely from anywhere in the United States or Canada.

Your responsibilities will include

• Architect scalable AI infrastructure for enterprise customers running large-scale training and inference workloads.

• Design production-ready ML platforms using Kubernetes, Slurm, Kueue, Ray, and other cloud-native technologies.

• Help customers optimize distributed training and inference across multi-node, multi-GPU environments.

• Guide customers through the full ML lifecycle, from experimentation and proof of concept through production deployment.

• Advise on GPU utilization, networking, storage, model serving, scalability, reliability, and cost optimization.

• Deliver technical presentations, workshops, architecture reviews, whitepapers, and webinars for technical and executive audiences.

• Build trusted relationships with strategic AI customers and translate technical requirements into measurable business value.

We expect you to have

• 5+ years of experience in Machine Learning Engineering, MLOps, AI Infrastructure, HPC, Solutions Architecture, or a similar customer-facing technical role.

• EXCELLENT customer communication throughout the GTM lifecycle, with strong consultative and presentation skills for both technical and non-technical audiences.

• Experience designing, operating, or supporting large-scale distributed AI infrastructure.

• Hands-on experience training, fine-tuning, or serving modern large language models.

• Experience running distributed workloads across multiple GPU nodes using NVLink, InfiniBand, or similar high-speed interconnects.

• Strong knowledge of the ML lifecycle, including data preparation, training, fine-tuning, inference, monitoring, and production operations.

• Experience transitioning ML workloads from proof of concept into highly available production systems.

• Experience with one or more training techniques, including pre-training, SFT, PEFT, LoRA, MoE, or RL/RLHF.

• Experience with production inference technologies such as vLLM, SGLang, NVIDIA Triton Inference Server, TensorRT-LLM, NVIDIA Dynamo, or DeepSpeed-Inference.

• Experience optimizing training and inference performance using metrics such as TTFT, TPS, ITL, request latency, RPS, MFU, throughput, GPU utilization, and cluster efficiency.

• Experience with profiling and observability tools such as NVIDIA Nsight Systems, NVIDIA Nsight Compute, PyTorch Profiler, or Perfetto.

• Proficiency with relevant technologies such as PyTorch, TensorFlow, Hugging Face, Docker, Kubernetes, Helm, Git, Slurm, Kueue, Ray, Terraform, or Ansible.

It will be an added bonus if you have

• Experience training multi-billion-parameter language models across distributed GPU clusters.

• Experience serving models with 30B+ parameters in production.

• Experience supporting AI infrastructure across hundreds or thousands of GPUs.

• Experience working with AWS, Azure, or Google Cloud.

• A background in high-performance computing.

• Experience optimizing GPU utilization and cluster performance at scale.

• Previous experience in a pre-sales or customer-facing Solutions Architect role.

• Familiarity with the NVIDIA AI Enterprise ecosystem.

Key Employee Benefits:

• Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.

• 401(k) Plan: Up to 4% company match with immediate vesting.

• Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.

• Remote Work Reimbursement: Up to $85/month for mobile and internet.

• Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.

Join Nebius Today! Pay Transparency

We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the

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