Member Of Technical Staff - ML Performance
About Us: Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference.
What this role actually needs.
About Us: Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. Requirements: - 5+ years of experience writing high-quality, high-performance code. - Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). - Familiarity with Nvidia GPU architecture and CUDA. - 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). Company context: Modal is the serverless compute platform built specifically for AI and Python workloads.
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 5+ years of experience writing high-quality, high-performance code.
- Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT).
- Familiarity with Nvidia GPU architecture and CUDA.
- 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).
Why this listing is more than a copied job post.
Member Of Technical Staff - ML Performance is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
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Compensation read
$150K - $350K is visible before the click, so candidates can compare the role against local market expectations before applying.
Work authorization read
Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
On-site roles in New York City should be compared against commute, local salary bands, and nearby employer demand.
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Next moves
- Tailor your resume around ai and llm instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to member of technical staff - ml performance is a high-signal on-site role in new york city, and it is most realistic for open to tn, h-1b, and opt candidates already in the united states.
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Watchouts
- $150K - $350K is visible, so calibrate your application around the posted range.
- Use open to tn, h-1b, and opt candidates already in the united states as part of your positioning so the recruiter does not have to infer it.
- Show concrete examples of succeeding in on-site environments.
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Apply through the employer source
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Source: jobs.ashbyhq.com · Source ID: af17da5e-23ca-4802-854d-5f0546e1ed32 · Confidence: 92/100 · Last checked: May 7, 2026
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