# Member of Technical Staff - ML Performance at Modal

> United States · Staff · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Amodal%3Aaf17da5e-23ca-4802-854d-5f0546e1ed32 (read 2026-11-15).

## Facts (observed)

- Company: [Modal](https://alderhq.app/companies/modal)
- Location text: New York; San Francisco
- Where it can be done from (inferred): United States (evidence: "Location: New York; San Francisco")
- Posted: 2026-04-21 (208 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-09
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/modal/af17da5e-23ca-4802-854d-5f0546e1ed32
- Skills listed (inferred): Docker

## Pay and sponsorship

- Posted pay: $200k–$350k per year (from the listing's pay field)
- Market band for similar posted roles (New York, n 43): p25 $236k, median $275k, p75 $279k
- H-1B filings at this company for similar roles, FY26: 1 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### 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 are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models toward higher throughput and lower latency, we’d love to hear from you!

### You May Be a Fit If

You have 5+ years of experience writing high-quality, high-performance code

You’ve worked with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT)

You’re familiar with NVIDIA GPU architecture and CUDA

You have experience with ML performance engineering (tell us a story about boosting GPU performance: debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc.)

### Nice-to-Have

Familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc.)

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Amodal%3Aaf17da5e-23ca-4802-854d-5f0546e1ed32 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.