# Customer Engineer

Remote from[USA](https://jobicy.com/job-region/usa.md), [Canada](https://jobicy.com/job-region/canada.md)Salary, yearly, USD 179,500                             - 224,300Department  [Technical Support](https://jobicy.com/categories/technical-support.md) Employment type Full Time, Job posted18 Jun 2026Apply before18 Jul 2026Views / Applies 1217 / 102 [About company](https://jobicy.com/company/nebius.md)

* Share About [Nebius](https://jobicy.com/company/nebius.md)

Nebius is the AI cloud company, delivering a unified platform that spans the complete AI journey from data and model training and tuning to production runtime and deployment.

[Computer Software](https://jobicy.com/company-category/software.md)
*  2023

Actively Hiring  Verified job posting This job post has been [manually reviewed](https://jobicy.com/tools/help-center/employee/how-does-jobicy-verify-the-legitimacy-of-remote-job-listings.md) for authenticity and compliance.

###  AI Summary

Nebius seeks a Customer Engineer to serve as a trusted technical advisor for strategic GPU Cloud clients. This role involves designing, deploying, and scaling AI solutions, optimizing GPU performance, and managing large-scale GPU workloads. The engineer will collaborate with sales and product teams to drive growth and enhance customer satisfaction. The position requires deep expertise in AI/ML, cloud infrastructure, and customer-facing technical support. It offers a competitive salary and comprehensive benefits, with remote work flexibility within the United States.

### Role DNA

Job Complexity Easy Hard Pace & Pressure Relaxed Fast-paced Autonomy Level Guided Full Ownership Communication Load Independent Highly Collaborative

AI Insight The role requires 5+ years of experience with deep technical knowledge in AI/ML, cloud services, and customer management, making it challenging but not the highest difficulty.

### Salary Analysis

Median  Above Market  USD201,900US Market USD120k – 200k 0 USD222k      AI Insight The offered salary range of $179,500 - $224,300 is above the market median for similar Customer Engineer roles, indicating a competitive compensation package that reflects the specialized AI/ML expertise required.

### Core Skills Required

[Cloud Infrastructure](https://jobicy.com/jobs?search_keywords=Cloud+Infrastructure.md) [AI/ML](https://jobicy.com/jobs?search_keywords=AIML.md) [GPU Computing](https://jobicy.com/jobs?search_keywords=GPU+Computing.md) [Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md) [Python](https://jobicy.com/jobs?search_keywords=Python.md) [Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md) [Ansible](https://jobicy.com/jobs?search_keywords=Ansible.md) [CUDA](https://jobicy.com/jobs?search_keywords=CUDA.md) [Customer Success](https://jobicy.com/jobs?search_keywords=Customer+Success.md) [Technical Advisory](https://jobicy.com/jobs?search_keywords=Technical+Advisory.md)

### Cover Letter Sample

Dear Hiring Team,

I am writing to express my interest in the Customer Engineer position at Nebius. With over 5 years of experience as a technical advisor in AI/ML and cloud infrastructure, I have a proven track record of helping clients design, deploy, and scale GPU-intensive workloads. My expertise in Kubernetes, Terraform, and Python, combined with a customer-centric approach, aligns perfectly with this role.

I have successfully managed relationships with key accounts, resolving complex technical issues and driving adoption of AI solutions. I am eager to bring my skills to Nebius and contribute to its innovative AI cloud platform.

Thank you for considering my application.

Copy

### Sample Interview Questions

Describe a time you optimized GPU performance for a customer's ML training workload. What steps did you take and what was the outcome?I worked with a customer using PyTorch on a multi-GPU setup. I identified that data loading was a bottleneck, so I implemented NVIDIA DALI and increased the number of data workers. This reduced training time by 40% and improved GPU utilization from 60% to 95%.How do you handle a situation where a customer disagrees with your technical recommendation?I listen to their concerns, ask clarifying questions, and provide data or benchmarks to support my recommendation. If we still disagree, I propose a small-scale proof of concept to test both approaches and let the results guide the decision.Explain your experience with Infrastructure as Code, specifically Terraform and Ansible.I have used Terraform to provision cloud resources like VPCs, instances, and Kubernetes clusters, and Ansible for configuration management, such as installing GPU drivers and setting up monitoring. I have also written modules and playbooks to automate recurring tasks.How do you prioritize multiple customer issues or feature requests simultaneously?I assess impact and urgency: critical production issues take precedence. For feature requests, I consider the number of customers affected and alignment with product strategy. I communicate timelines to customers and update them on progress.Describe your experience with Kubernetes in production environments, especially for AI/ML workloads.I have deployed and managed Kubernetes clusters with GPU nodes using node selectors and device plugins. I set up Kubeflow for ML pipelines and used tools like Helm for deployments. I also implemented monitoring with Prometheus and Grafana to track resource usage and performance.  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.

## The role

We are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from the United States.

Your responsibilities will include:

* Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
* Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
* Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
* Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
* Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

* Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
* Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
* Experience with Kubernetes and Python programming.
* Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
* Customer-centric approach with a proven ability to build trust and foster long-term relationships.
* Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

* Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
* Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
* Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
* Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
* Proven experience mentoring technical teams and driving team growth.
* Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

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 candidate is hired, and geographic location, consistent with applicable law.

Base Compensation Range$179,500—$224,300 USD

Benefits & Perks:

* 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

What’s it like to work at Nebius:

Fast moving – Bold thinking – Constant growth – Meaningful impact – Trust and real ownership – Opportunity to shape the future of AI

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.

If you need accommodations during the application process, please let us know.

Show more

[Apply now >](https://jobicy.com/jobs/147134-customer-engineer.md)

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