Head of Engineering GPU
Scaleway is hiring a Head of Engineering GPU in Paris, France. Level rates it ; you can apply on Scaleway.
Level's read on this job
- Little AI ββββ is how Level rates this role: aI is not part of the work.
- Level classifies it as an executive role.
- Level lists 32 other open roles at Scaleway.
AI in this role
WHY WE NEED YOU ?
As our GPU Cloud business continues to scale, we are strengthening our engineering leadership to support the deployment and operation of increasingly large and complex GPU clusters.
Your mission will be to lead our Support Engineering, HPC, and SRE teams, own key technology and architecture decisions, and ensure that our most strategic GPU infrastructure projects are successfully designed, delivered, and operated.
You will also play a critical role in validating the technical feasibility of commercial proposals and ensuring that the commitments we make to customers can be delivered reliably on our sovereign cloud infrastructure.
YOUR FUTURE TEAM
We work in a collaborative and international environment where the diversity of Scalers, combined with a strong culture of knowledge sharing, helps us bring ambitious projects to life.
You will lead an organization of 14 engineers across two squads, each managed by an Engineering Manager reporting directly to you.
As part of the broader GPU Cloud organization, reporting to the SVP GPU Cloud, you will work closely with GTM, Operations, Service Management, Product, and other engineering teams to build and operate large-scale AI and HPC infrastructure.
YOUR DAILY ROUTINE
Tasks
- Lead the Support Engineering, HPC, and SRE organizations, directly managing two Engineering Managers responsible for 14 engineers
- Own the technical strategy, architecture, and key technology choices for GPU Cloud infrastructure
- Review and validate the technical and service dimensions of strategic commercial proposals, ensuring commitments are realistic and deliverable
- Oversee the design, deployment, and operational readiness of new GPU clusters
- Drive the evolution of our cluster management, capacity management, automation, and operational capabilities
- Ensure the reliability, scalability, performance, and maintainability of our GPU infrastructure
- Provide technical leadership on complex AI and HPC infrastructure projects
- Build strong alignment between Engineering, GTM, Product, and Operations
- Develop the engineering organization through clear direction, effective delegation, coaching, and long-term team development
- Establish and maintain high standards of engineering rigor, operational excellence, and technical decision-making
ABOUT YOU
HARDSKILLS:
- 10+ years of experience in infrastructure engineering, including significant experience leading senior technical teams and managers
- Proven experience designing, deploying, or operating large-scale infrastructure and compute clusters
- Familiarity in GPU and/or HPC environments, ideally involving NVIDIA and AMD technologies
- Strong understanding of distributed infrastructure, cluster architecture, reliability, and production operations
- Experience with orchestration, provisioning, and observability technologies such as Kubernetes, Proxmox, Warewulf, Prometheus, and Grafana
- Experience with high-performance and distributed storage technologies such as Lustre, DDN, and VAST Data
- Ability to assess architectural trade-offs and translate complex technical constraints into clear engineering and business decisions
SOFT SKILLS:
- Strong leadership skills with the ability to lead experienced engineers and Engineering Managers
- Ability to navigate complex technical, organizational, and business situations
- High level of rigor and a strong sense of ownership
- Excellent organizational, prioritization, and planning skills
- Strong communication and stakeholder-management abilities
- Ability to synthesize complex engineering topics and communicate them clearly to both technical and non-technical stakeholders
- Comfortable making decisions in fast-moving environments with high technical and operational stakes
WHAT YOU WILL FIND AT SCALEWAY
- Hybrid work: We offer up to 3 days of remote work per week.
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Offices: Our offices are spacious, dynamic workspaces with bold design, conveniently located near public transport. Most of our offices feature outdoor spaces (terraces) and bike parking facilities.
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Dining: Our chef provides a healthy meal service at the headquarters, and breakfast is available across all our sites year-round. Scalers working from regional sites enjoy a Swile card for lunches.
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Well-being commitments: Whether itβs access to a gym, daycare places, or discounted services for caring services, Scaleway is committed to supporting Scalers in maintaining a balanced life.
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International environment: With dozens of nationalities, Scaleway offers a stimulating environment where English is as widely spoken as French.
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Career & Mobility: Our managers value internal mobility, and opportunities to transition to other entities within the Iliad Group are accessible to all Scalers.
π Why join the Scaleway adventure?
β A rich and diverse product offering: Scaleway offers over 100 public cloud products in IaaS, PaaS, and AI.
β A cutting-edge technical environment: Scaleway provides modern infrastructures, including high-performance bare metal servers, to tackle exciting technical challenges.
β Commitment to responsible cloud: Scaleway is dedicated to a more responsible cloud, with data centers powered solely by renewable energy since 2017, minimizing our ecological footprint and holding top-level certification.
π THE NEXT STEPS β¦
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HR discovery call (30 min)
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Interview with to understand your technical skills and approach to the role (45 min)
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Technical interview with CTO to validate your expertise (1h)
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Interview with Management to deepen discussions and assess your fit with the team (45 min)
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HR interview to tour our offices and meet your future colleagues
How we rate this
Head of Engineering GPU at Scaleway rates 35 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ββββ Builds AI80 to 100
- ββββ Works on AI60 to 79
- ββββ Uses AI40 to 59
- ββββ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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