Role OverviewFlexion is building the autonomy stack for humanoid robots. We are looking for an experienced ML engineer to join our infrastructure team and take ownership of our GPU compute platforms.
What You Will Do
You will own the design, bring-up, operation, and optimization of performant clusters, work with AI engineers to optimize their training speed and hardware utilization, and influence strategic compute planning.
Why It Might Be a Fit
This role will put you at the heart of Flexion's AI development and allow you to directly impact the execution of our ambitious roadmap. You will closely collaborate with the company's leadership, engineers of the infrastructure team, and AI engineers across the company.
Requirements
- Degree in Computer Science, Electrical Engineering, or Software Engineering (or equivalent practical experience)
- Significant industry experience
- Hands-on experience with the training or inference of large models (billions of parameters) on distributed multi-node GPU hardware
- Proficiency in Python and working knowledge of PyTorch
- Deep understanding of distributed training concepts (DDP, FSDP, NCCL)
- Experience with at least one cloud platform (AWS, GCP, Azure, or neoclouds) or large-scale on-premises GPU infrastructure
- Experience with job scheduling and orchestration tools: Slurm and/or Kubernetes/KubeRay
Benefits
- Competitive compensation
- Joining a leading robotics team & exposure to never-done-before research
- Energetic, collaborative culture with a bias for action and regular community events
- Enhanced pension plan
- Relocation & permit sponsorship
- Enhanced holiday & paid leave perks
- 401(k) with company contributions
- Health, dental & vision coverage with the flexibility to choose your own plan
- Open PTO policy & paid company holidays
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