1 year ago
Base Salary
$150k - $230k/yr
Responsibilities
- Ship bug fixes, features, and automation that improve the experience for Modal users.
- Help developers and ML engineers debug, optimize, and architect workloads through Slack, email, and calls.
- Design tooling, dashboards, and automated workflows that make customer support efficient at scale.
- Translate recurring customer issues into documentation fixes, API changes, and feature proposals.
- Write examples, build demos, and publish technical content while contributing to open source.
Requirements
- Demonstrated depth in either low-level infrastructure or ML/AI, with working familiarity in the other area.
- Experience with operating systems, file systems, networking, performance profiling, cluster management, and distributed systems.
- Experience training models, optimizing inference, working with GPUs, or building ML infrastructure.
- Ability to automate manual processes and build production-quality engineering solutions.
- Strong communication skills for explaining systems issues, writing bug reports and documentation, and collaborating internally.
Tech Stack
Seaborn
Categories
Solutions Engineering
About Modal
Modal builds a serverless compute platform for AI and data workloads, offering instant GPU access, sub-second container starts, and native storage to run inference, fine-tuning, and batch jobs. It sells a usage-based cloud service to developers and ML teams to deploy generative models and pipelines. Privately held and headquartered in New York City, its customers include companies like DoorDash and Ramp.