Staff Software Engineer (Compute Efficiency)
Isomorphic LabsVisit Isomorphic Labs website
AI-first drug design and development company building a unified drug-design engine to advance new medicines.
London, United Kingdom
Funding history
Investors
About Isomorphic Labs
Isomorphic Labs uses predictive and generative AI models, computational biology, and drug-design expertise to develop therapeutics across partnered and internal programs.
Skills
Candidate Availability
About the Role
You will design, deploy, and scale observability systems and telemetry pipelines to monitor compute efficiency, hardware health, and workload goodput across distributed clusters. You will find compute waste, improve accelerator utilization and ML run reliability, integrate new hardware, harden cloud infrastructure, and contribute to core technical decisions with ML, platform, and science teams.
Requirements
- Real-world experience operating, monitoring, and debugging infrastructure for large-scale AI/ML workloads
- Experience in cloud compute infrastructure design, preferably GCP
- Strong programming skills
- Significant experience deploying in Kubernetes at scale
- Familiarity with Nvidia GPU generations
- Proven track record building production observability and telemetry stacks
Responsibilities
- Design, deploy, and scale observability systems and telemetry pipelines for fleetwide compute efficiency, hardware health, and goodput
- Drive hardware efficiency and node reliability and integrate new hardware
- Identify compute waste and bottlenecks and optimize accelerator utilization
- Instrument and improve canonical efficiency metrics for training and inference runs
- Improve reliability of ML runs
- Operate, maintain, and harden research, development, and production cloud infrastructure and clusters
- Collaborate with science, research, product, business development, and operations teams
- Contribute to core technical decisions on tooling, infrastructure, and architecture
Benefits
- Hybrid working model