Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 3
IaC @ 3
Python @ 3
GCP @ 3
MLOps @ 3
Leadership @ 3
AWS @ 3
Azure @ 3
Communication @ 3
Networking @ 3
GDPR @ 3
API @ 3
Technical Leadership @ 3
Databricks @ 3
Snowflake @ 3
Compliance @ 3
Cloud Computing @ 3
GPU @ 3
Observability @ 3
AI @ 3
RAG @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Nebius is leading a new era in cloud computing to serve the global AI economy. We create tools and resources to help customers solve real-world AI/ML challenges at massive GPU cloud scale without massive infrastructure costs or large in-house AI teams. Headquartered in Amsterdam and listed on Nasdaq, Nebius has R&D hubs across Europe, North America, and Israel and a global team of over 800 employees, including 400+ engineers.
Customer experience
Customer experience 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 will work with advanced GPUs such as H200, B200 and GB200 and modern ML frameworks, influencing the development of the Nebius AI Cloud at the intersection of infrastructure and AI.
The role
You will serve as the technical interface between Nebius and strategic technology partners (data platforms, MLOps vendors, AI frameworks, ISVs building on GPU infrastructure). This is a hands-on engineering and integration role: design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius' product roadmap and drive deep technical collaboration across partner ecosystems.
You are welcome to work remotely from the United States or Canada.
Responsibilities
- Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product
- Design and architect high-impact integration solutions that deliver clear joint customer value
- Build and maintain reference implementations and production-grade integrations
- Define enterprise-ready integration patterns (networking, security, compliance, observability)
- Translate partner and customer feedback into actionable product and roadmap requirements
- Enable partner teams through technical documentation, training, and demo environments
- Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting
Requirements
- 7+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies
- Strong expertise in cloud infrastructure
- Hands-on experience with GPU-accelerated AI/ML workflows (training, inference, MLOps)
- Proven background in integration architecture (API design, data pipelines, security, observability)
- Experience with Python and Infrastructure as Code (IaC) tools
- Excellent communication skills with the ability to engage technical and non-technical stakeholders
Nice to have
- Track record of building or scaling partner technical programs or ecosystems
- Experience with Snowflake, Databricks, AWS, Azure, or GCP
- Background in ML lifecycle (training pipelines, fine-tuning, inference optimization, RAG)
- Understanding of compliance standards: SOC 2, HIPAA, GDPR, FedRAMP
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
- Company-paid short-term, long-term, and life insurance coverage
- Competitive salary and equity, opportunities for professional growth, flexible working arrangements
Compensation
We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on experience, skills, and location.