Member of Technical Staff (TPM, Compute)
Perplexity · San Francisco
About this role
## Overview Perplexity is looking for a **Technical Program Manager** to own how we plan, bring online, and run the **GPU compute** behind every product. You’ll work across engineering, research, finance, and cloud/neocloud providers to forecast capacity needs, launch new capacity into production, and ensure the fleet performs reliably, efficiently, and cost-effectively. ## What You’ll Do - Partner with Finance on a **3–12 month compute demand forecast**, driven by customer growth, model releases, and post-training/evaluation plans (not just trend lines) - Turn forecasts into decisions with Finance and engineering leadership on **commitments and budget**, ensuring new capacity fits the plan before committing - Bring new capacity online and lead transitions (e.g., **contract → production**), including provider onboarding, acceptance criteria, migration, and decommissioning - Build a single, trusted view of the fleet: **capacity, cost, allocation, uptime**, and **reliability/utilization** by provider and workload - Drive daily **utilization, reliability, and cost-efficiency** as core metrics—reclaim idle capacity and surface trade-offs proactively - Own inference and compute requests end-to-end: triage and resolve GPU/deployment/quota requests, and build **self-serve** paths so routine requests don’t require manual intervention - Manage compute provider relationships using **scorecards and regular reviews** (reliability, support, delivery) and use insights to shape long-term provider strategy - Partner with engineering and research/finance on capacity decisions across **training, batch inference, and real-time production inference** - Build the “operating system” for compute: processes and tooling to **request, plan, allocate, and track** compute with clear ownership ## Qualifications - **6+ years** in technical program management, capacity planning, or infrastructure operations in cloud environments; leading programs across teams and vendors - Direct experience with **GPU/accelerator fleets** across training and inference workloads - Experience working with **cloud or neocloud providers** on reserved capacity, commitments, onboarding, or vendor performance management - Experience with **infrastructure cost modeling**, unit economics, or cost attribution in partnership with Finance - Technical depth in **cluster management, scheduling, and orchestration**, plus the data skills to build forecasts and dashboards - Strong judgment to surface hard trade-offs and communicate clearly to engineers and executives - Thrives in a small, agile team with initiative and ownership in an environment with limited precedent
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.