Member of Technical Staff (TPM, Inference)
At a glance
Senior Software Engineering role at Perplexity. San Francisco · full-time · $170,000–$265,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Advance the inference platform roadmap, covering request routing, quotas, usage controls, reliability and observability
- Coordinate provider onboarding and launch preparation with internal engineering and product teams as models and capacity come online
- Track latency, throughput, uptime and cost together, making the tradeoffs visible during execution
- Run model release and optimization programs, including launch-day work and post-release checks across infrastructure, performance and product
- Create release routines, dashboards and checklists, and align GPU capacity decisions with cost and vendor limits
What you bring
- At least six years in technical program management or product management
- You have managed technical programs or products involving infrastructure, distributed systems or ML serving
- You have worked directly with production LLM or ML inference systems and understand serving performance and reliability
- You can use metrics to weigh latency, throughput, uptime and cost while coordinating internal teams and external partners
Who this fits
This senior role suits someone who can take ownership in a small, agile team and build operating practices where there is little precedent. You’ll coordinate across model providers and internal teams, with the role based in San Francisco.
From the employer
Perplexity is looking for a technical program manager to be the connective tissue between our model providers, engineering, and product teams, driving our core inference platform forward.
Perplexity runs one of the highest-throughput inference stacks in the industry, serving Ask, Computer, and API traffic across a large and constantly shifting portfolio of first-party and third-party models. This role sits at the intersection of product, engineering, and finance: you'll orchestrate across model providers and internal teams to keep new models and capacity moving smoothly into production, while executing the roadmap for the inference platform itself. The ideal candidate has strong technical judgment, thrives coordinating across teams and external partners with competing timelines, and is energized by building the operating model for a function that doesn't have much precedent yet.
Our Mission
Perplexity's mission is to power curiosity. Curious people are the people who drive change in the world. Driving change is a continuous cycle of learning, building, and integrating.
Learn: curious people constantly learn new things by asking more. They question the status quo in their own expertise and they constantly learn outside of it. Research is essential to them and never ending.
Build: curious people make and create things, to show the world their new answers to problems no one else ever questioned. They take action on what they've learned. Makers need tools to create their products, their companies, their reality.
Integrate: they must interact with the world as it is to drive change and adoption. True leaders do not simply build something and hope. They must have armies of agents and workers who can constantly work in millions of small ways.
What You'll Do
Execute the roadmap for the inference platform request handling, rate limits and quotas, usage controls, and the reliability and observability surface engineering and product teams depend on
Be the connective tissue between model providers and Perplexity's engineering and product teams coordinating onboarding, launch readiness, and rollout for new models and capacity
Drive latency, throughput, uptime, and cost-efficiency as core execution metrics, surfacing tradeoffs between them rather than letting them become side effects
Run the operating model for model-release and optimization programs, including day-zero launches, across performance engineering, infrastructure, and product teams
Lead cross-functional delivery for inference-stack changes, from planning through launch and post-launch validation
Build the mechanisms that make releases predictable rituals, dashboards, launch checklists so inference releases stay low-risk at Perplexity's scale
Partner with GPU capacity and compute teams to reconcile execution decisions against cost, capacity, and vendor constraints
Qualifications
Strong experience with technical program management or product management in infrastructure, distributed systems, or ML/model-serving products
Direct experience with production LLM or ML inference understanding what makes serving fast, reliable, and cheap rather than just what a roadmap slide says about it
Comfort orchestrating across external partners and internal engineering teams with competing priorities and timelines
Experience with data and metrics, and the judgment to surface difficult tradeoffs between latency, throughput, uptime, and cost
Thrives in a small, agile team; has initiative and desire for ownership without much precedent to lean on
6+ years of combined technical program management or product management experience
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