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Active10mo ago

Member of Technical Staff - Product (Backend)

Modal·📍 San Francisco, California, United States

Employment

FULL TIME

Work mode

On-site

Experience

SENIOR LEVEL

Salary

$150K – $300K/yr

Pay vs market · Bottom quarter

This job's pay ($225,000 a year at the midpoint) is higher than about 15% of 119 salary-listed Member of Technical Staff jobs in San Francisco in the last 12 months; their median is $285,000.

Salary data →

Role overview

Job description

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for strong backend engineers who love building developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. You May Be a Fit If: You’ve built and shipped modern web applications end-to-end You’re comfortable working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics You have deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes and training and inference for large language models (LLMs) and diffusion models You have experience with at least one of the following: billing/payments systems, B2B SaaS tooling, enterprise software, or LLM/diffusion model inference and training workloads You have strong product instincts and think about customer problems, not just tickets You’re able to participate in our on-call rotation and respond to production incidents You make good tradeoffs between shipping fast and building for scale You’re able to work in person in our NYC or SF office

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About this listing

  • Source: Modal's official careers site · still listed there on 10 Nov 2026
  • Posted 9 Jan 2026

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Role market pulse

How Member of Technical Staff demand looks in United States

71/100 · rising

Live jobs

276

Posted 30d

252

30d movement

+1382.4%

Remote share

23.9%

Salary listed

90.9%

Salary trend 1Y

Not enough history

What they are looking for

Skills & requirements

Qualification

Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models; Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads

Department · Engineering Department

Hiring company

Modal

Technology

Cloud infrastructure for teams that develop, train, and serve AI applications at scale.

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