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Member of Technical Staff - Product (Backend)

Modal Labs

New York, NYFull-time$150–300K/yrPosted 7mo agoVerified open 3 days ago

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At a glance

Compensation
$150–300K/yr
Location
New York, NY
Schedule
Full-time
Work Authorization
Not specified

Job overview

Modal Labs is hiring a Member of Technical Staff - Product (Backend). Modal Labs is building a new AI infrastructure layer and seeks strong backend engineers to create developer tools for large AI companies. The role involves building scalable systems, working across the full stack, implementing observability for massive workloads, and handling billing, SaaS, or model inference and training, while participating in on‑call rotations.

Key focus areas include Build and ship modern web applications end‑to‑end., Develop across the stack using TypeScript, Python, and ClickHouse., and Design and implement observability tools and patterns for large‑scale AI workloads..

Successful candidates bring Building And Shipping Modern Web Applications End-To-End, Participate In On-Call Rotation, and Respond To Production Incidents. Important skills include TypeScript, Python, ClickHouse, Observability Tools, Observability Patterns, and Product Instincts. Preferred (not required): Billing Systems, LLM Inference, LLM Training Loads, and Diffusion Models Training Loads.

Skills & qualifications

RequiredNice to have

Skills

TypeScriptPythonClickHouseObservability ToolsObservability PatternsProduct InstinctsTradeoff ManagementBilling SystemsPayments SystemsB2B SaaS ToolingEnterprise SoftwareLLM InferenceDiffusion Models InferenceLLM Training LoadsDiffusion Models Training Loads

Qualifications

Building and Shipping Modern Web Applications End-to-EndParticipate in on-Call RotationRespond to Production IncidentsWork in-Person in NYC or SF Office

Full job 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 Lovable , 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 recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.

Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

The Role: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day.

Requirements:

  • Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building.

  • Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics.

  • 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.

  • Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads.

  • Strong product instincts; you think about customer problems, not just tickets.

  • Ability to participate in on-call rotation and respond to production incidents.

  • Ability to make good tradeoffs between shipping fast and building for scale.

  • Ability to work in-person in our NYC or SF office.

You've read the whole posting — now see how you match it.

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