Member of Technical Staff - Machines
Modal · San Francisco · New York
- Level
- Staff
- Type
- full-time
- Mode
- On-site / hybrid
- Posted
- 2026-09-22
- Compensation
- $250K – $300K
- Team
- Engineering, Engineering
Role 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.…
Technologies named in the posting
How Rolefit scores this role
- Stack overlap (50%). Every technology named in the posting is compared with your selected stack, weighted by how rare it is across the whole index — a niche match counts for more than Docker.
- Seniority fit (16%). The level in the posting is compared with the level assessed from your years and depth.
- Title alignment (16%). Whether the role is actually pitched at your field rather than adjacent to it.
- Freshness and filters (18%). Newer postings, your work type and your target region all move the score.
The score you see on a shortlist is specific to you — the same posting scores differently for a different stack. Run the assessment once and this role either makes your top 30 or it does not.
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