Senior ML Infra Engineer for GPU Compute

Flexion Robotics; Zürich; On-site; CHF 140,000 - 190,000; Full time

Benefits offered by this job

Enhanced pension plan

Relocation sponsorship

Enhanced holiday & paid leave perks

Zurich office facilities

Job summary

Flexion Robotics is seeking an experienced ML engineer to lead the design, bring-up, operation, and optimization of GPU compute platforms. You will collaborate with AI engineers to accelerate training, improve hardware utilization, and influence compute strategies across cloud and on-prem infrastructures.

This on-site role offers a chance to shape a leading robotics autonomy stack. You will manage cluster provisioning, profiling, and tooling, while contributing to the core ML libraries and

Qualifications

• Expertise in training or inference of large models on distributed multi-node GPU hardware.
• Strong Python and PyTorch skills with production experience.
• Experience with cloud or on-prem GPU infrastructure and multi-cloud strategies.
• Familiarity with job scheduling/orchestration tools (Slurm, Kubernetes).

Responsibilities

• Architect, run and continuously improve existing and future cloud-based GPU clusters.
• Help AI engineers optimize training workloads and maximize hardware utilization.
• Contribute to GPU compute strategies and multi-cloud planning with the AI teams.
• Raise the bar on engineering practices, including testing, code quality, and documentation.

Skills

Python

PyTorch

Distributed training

Cloud platforms

Slurm

Kubernetes

Large models training/inference

Education

Degree in Computer Science, Electrical Engineering or Software Engineering

Tools

Slurm

Kubernetes

Job description

Flexion Robotics is seeking an experienced ML engineer to lead the design, bring-up, operation, and optimization of GPU compute platforms. You will collaborate with AI engineers to accelerate training, improve hardware utilization, and influence compute strategies across cloud and on-prem infrastructures.

This on-site role offers a chance to shape a leading robotics autonomy stack. You will manage cluster provisioning, profiling, and tooling, while contributing to the core ML libraries and