Forward Deployed Engineer (GPU Clusters)
Together AI · San Francisco, CA · Customer Success
About this role
Together AI is hiring a mid-level Field Engineer in the software engineering function based in San Francisco, CA. The posting calls out experience with Python, Bash, Kubernetes, Ansible. Compensation is listed at $270,000–$300,000 per year.
- Role
- Field Engineer
- Function
- software engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- Customer Success
More roles at Together AI
Job description
from Together AI careersAbout the role
As a Forward Deployed Engineer (FDE) focused on large scale GPU clusters, you will be a hands-on technical partner to our strategic customers – the world’s leading AI model builders. You will partner with our SAs as a deep-domain specialist in large-scale infrastructure, storage, high-performance networking, and cluster orchestration. As key contributors to the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption for our strategic customers, and guide tailored optimization efforts - directly impacting company growth and the hardening of our core platform.
Responsibilities
- Cluster Hardening & Validation: Design and execute rigorous pre-handover test suites (NCCL, DCGM, GPU Burn) to ensure clusters are stable under the extreme stress of multi-node training.
- Technical Partnership: Act as the primary technical point of contact for model labs, helping them tune their orchestration layer (Kubernetes or SLURM) for maximum throughput.
- Infrastructure Optimization: Profile and debug low-level bottlenecks in InfiniBand (IB) fabrics, NVLink topologies, and high-performance storage systems.
- Opinionated Onboarding: Build reference designs and "out-of-the-box" configurations for training frameworks to reduce customer time-to-train.
- Benchmarking & Migration: Lead complex benchmarking exercises to demonstrate the performance impact of migrating to new hardware families or Together AI’s optimized infrastructure.