About Synlogiq
At Synlogiq, we connect exceptional engineering talent with innovative companies building products that make a real impact. We partner with ambitious organizations to help them grow high-performing engineering teams capable of solving complex technical challenges.
About the Role
Location: On-site, Austin, TX or Toronto, ON
This role sits at the intersection of infrastructure automation, hardware validation, Kubernetes platforms, and large-scale AI infrastructure.
The team is responsible for building and validating the infrastructure used to deploy and operate Tenstorrent AI systems across data center environments. The work involves automation, infrastructure tooling, deployment validation, system diagnostics, troubleshooting, and testing of large-scale compute environments.
The ideal candidate is typically someone with approximately 3-10 years of relevant hands-on experience working with bare-metal infrastructure, Linux systems, Kubernetes platforms, large-scale infrastructure environments, or GPU/AI infrastructure. Direct GPU infrastructure experience is highly valued, though candidates with strong bare-metal, systems, or infrastructure engineering backgrounds may also be successful in the role.
*For this role candidate must be eligible to work in the US or Canada without visa sponsorship.*
What You’ll Do
- Building internal tooling and automation for infrastructure deployment and validation.
- Developing frameworks and scripts for infrastructure testing, diagnostics, and health validation.
- Supporting deployment validation across compute clusters and infrastructure environments.
- Troubleshooting hardware, networking, platform, and infrastructure-related issues.
- Performing root-cause analysis across hardware, networking, operating system, and platform layers.
- Working closely with infrastructure, networking, hardware, and software engineering teams.
- Improving infrastructure reliability, operational workflows, and validation coverage.
What We’re Looking For
Strongly relevant experience includes:
- Bare-metal infrastructure environments.
- Data center infrastructure, cluster management, or infrastructure validation.
- Experience operating, validating, or troubleshooting infrastructure at scale.
- Linux systems administration and debugging.
- Networking fundamentals and infrastructure troubleshooting.
- Kubernetes operations, troubleshooting, and platform engineering.
- Infrastructure automation using Python, Go, or similar languages.
Particularly valuable experience includes:
- GPU infrastructure
- AI/ML infrastructure platforms
- Hardware or accelerator validation
- High-performance networking and network debugging
- Slurm
- Ray / KubeRay
- NCCL
- GPU Direct RDMA
- RoCE / InfiniBand