Member of Technical Staff - Product (backend)

Modal Modal · Data AI · New York, NY · Engineering

Backend engineer for an AI infrastructure company providing GPU access, instant container startups, and storage for training, batch jobs, and low-latency inference. The role involves building modern web applications end-to-end, working across the stack (TypeScript, Python, ClickHouse), and focusing on observability for large-scale AI workloads.

What you'd actually do

  1. Building for things at scale, but also for new AI workflows that change every day.
  2. Building and shipping modern web applications end-to-end.
  3. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics.
  4. 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.
  5. Ability to participate in on-call rotation and respond to production incidents.

Skills

Required

  • TypeScript
  • Python
  • ClickHouse
  • observability tools and patterns
  • billing/payments systems
  • B2B SaaS tooling
  • enterprise software
  • LLM / diffusion models inference and training loads
  • product instincts
  • on-call rotation
  • incident response
  • tradeoffs between shipping fast and building for scale

What the JD emphasized

  • production AI workloads
  • training and inference for large language (LLM) and diffusion models
  • on-call rotation and respond to production incidents

Other signals

  • thousands of customers who rely on us for production AI workloads
  • building for things at scale
  • serving low-latency inference
  • training and inference for large language (LLM) and diffusion models