---
title: 'Member of Technical Staff - Platform Engineering at Modal'
canonical: 'https://feeny.ai/job/member-of-technical-staff-platform-engineering-modal-new-york-97322xwz37ts'
type: 'job'
last_seen: '2026-09-15'
---

# Member of Technical Staff - Platform Engineering at Modal

- **Company:** Modal
- **Location:** New York, NY
- **Employment:** full-time
- **Posted:** 2026-01-19
- **Last confirmed live:** 2026-09-15
- **Apply:** https://jobs.ashbyhq.com/modal/84467a68-6876-4730-9d80-6c6f3d0c2d71

## 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](https://modal.com/blog/lovable-case-study), [Ramp](https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal), 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](https://modal.com/blog/modal-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](https://github.com/mwaskom/seaborn),[Luigi](https://github.com/spotify/luigi)), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include:

- Identifying architectural changes to improve reliability and performance.
- Fostering a culture of reliability across Modal’s engineering organization.
- Defining and implementing operational processes such as deployments, upgrades, etc.
- Operating systems like Kubernetes, Postgres, Redis, etc.
- Participating in on-call rotations, and responding to production incidents.

Requirements:

- 5+ years of experience writing high-quality production code.
- 2+ years of on-call experience for critical production services.
- Strong cloud skills, and deep familiarity with at least one hyperscaler cloud (AWS preferred).
- Familiarity with auto scaling, fleet management, and capacity planning at scale.
- Experience operating databases, monitoring, CI/CD, and other infrastructure, at scale
- Experience owning and scaling Kubernetes clusters to thousands of nodes a plus.
- Experience with systems safety research (e.g. STAMP) and control theory a plus.
- Ability to work in-person in our NYC or Stockholm offices.

## About Modal

## Company Overview
- **One-liner**: Modal provides high-performance AI infrastructure—a serverless, globally distributed GPU cloud for inference, training, sandboxes, and agent workloads.
- **Entity Type**: Private (raised over $466M, Series D from top-tier investors)
- **Headquarters**: New York, NY, USA (with offices in Stockholm, Sweden and San Francisco, CA, USA)
- **Founded**: Not publicly available in provided sources
- **Founders**: Erik Bernhardsson and Akshat Bubna

## Core Business
- Primary industry: Cloud infrastructure / AI compute / Developer tools
- Target customers: Developers and engineering teams building AI/ML products (B2B, from startups to enterprises)
- Mission or purpose: “Make it easier to iterate and ship applications for data, AI, and machine learning” and “Make cloud development work like magic.”

## Products & Services
- **[Modal Runtime](https://modal.com/)** – Serverless container platform with custom file system, scheduler, and container image builder. Sub-second cold starts and instant autoscaling from 0 to 1000+ GPUs.
- **[Modal Sandboxes](https://modal.com/)** – Isolated, ephemeral environments for running untrusted code (e.g., coding agents, RL rollouts). Programmatically spin up fresh environments with custom images.
- **[Modal Inference](https://modal.com/)** – Globally distributed inference with sub-10ms overhead latency, support for token streaming, WebRTC, WebSocket. Supports LLMs, audio, image/video generation.
- **[Modal Training](https://modal.com/)** – Fine-tuning and multi-node training on H100s, A100s, B200s with gang scheduling and InfiniBand networking. Single line of code to scale from single-GPU to multi-node clusters.
- **[Modal Batch / Async Inference](https://modal.com/)** – Run evaluations, embeddings, re-ranking, dataset generation at scale, thousands of GPUs fully parallel.
- **[Modal SDK](https://modal.com/)** – Python SDK that lets developers define infrastructure and workloads in code, then ship to the cloud.

## Market Standing
- **Valuation**: $4.65B (as of 2026, per [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-modal-2026))
- **Key Metric**: Total funding raised – over $466M (per [modal.com/company](https://modal.com/company))
- **Notable Investors/Partners**: General Catalyst, Redpoint Ventures, Lux Capital, Amplify Partners, Creandum (per [modal.com/company](https://modal.com/company))
- **Growth Signals**: ~150 employees (2026); global offices in New York, Stockholm, San Francisco; rapid hiring across engineering, GTM, and G&A roles; strong traction in inference, training, and agent infrastructure.

## Competitive Advantages
- **Deep infrastructure stack**: Custom file system, container runtime, scheduler, and image builder built from scratch to optimize AI workloads.
- **Developer experience**: “Stay in Python, ship to the cloud” – composable primitives that specify everything from logic to hardware in one code file.
- **Instant elasticity**: Scale from zero to 1000+ GPUs in seconds, pay only for compute used (no reserved capacity).
- **Global GPU access with low latency**: Sub-10ms overhead for online inference via globally distributed compute.
- **Compliance and security**: SOC 2 and HIPAA compliant, data residency controls, battle-tested isolation for untrusted code.

## Strategic Focus
- **AI-native runtime**: Deepening support for inference, fine-tuning, reinforcement learning, and agent workflows.
- **Scaling for agents**: Developing sandboxes and execution layers purpose‑built for interactive coding agents and long‑running RL rollouts.
- **Expanding global capacity**: Adding GPU availability across more regions, leveraging elastic cloud capacity.
- **Enterprise readiness**: Investing in security, governance, team controls, and data residency to serve larger customers.

## Why Work Here
- **Culture and team**: Founded by engineers who created open‑source tools (Seaborn, Luigi); team includes academic researchers, olympiad medalists, and experienced engineering leaders. Flat, high‑trust environment.
- **Location / flexibility**: Offices in New York, Stockholm, and San Francisco; likely hybrid/remote‑friendly (many roles list multiple locations).
- **Compensation and growth**: Transparent salary culture (as highlighted in 2026 profile); strong growth trajectory backed by $466M in funding and a $4.65B valuation.
- **Perks**: $30/month free compute for personal projects (customer benefit, likely similar for employees); focus on developer experience and “magic.”

## Sources
1. [modal.com](https://modal.com/)
2. [modal.com/company](https://modal.com/company)
3. [jobs.ashbyhq.com/modal](https://jobs.ashbyhq.com/modal)
4. [linkedin.com/company/modal-labs](https://www.linkedin.com/company/modal-labs)
5. [jobsbyculture.com/blog/working-at-modal-2026](https://jobsbyculture.com/blog/working-at-modal-2026)

## Other roles at Modal

- [People Lead, UK](https://feeny.ai/job/people-lead-uk-modal-london-w4prwqknpwp5) — London, United Kingdom
- [Member of Design Staff - Brand](https://feeny.ai/job/member-of-design-staff-brand-modal-new-york-ccfxde25jatb) — New York, NY
- [Detection and Response Engineer](https://feeny.ai/job/detection-and-response-engineer-modal-new-york-93gcmptvvjtd) — New York, NY
- [Revenue Operations](https://feeny.ai/job/revenue-operations-modal-san-francisco-tpwq37mk240a) — San Francisco, CA
- [Regional Director](https://feeny.ai/job/regional-director-modal-new-york-ywxxargrqp0g) — New York, NY
- [ML Research Intern](https://feeny.ai/job/ml-research-intern-modal-new-york-67tppdwsng1t) — New York, NY
- [Member of Technical Staff - Research, Post-Training](https://feeny.ai/job/member-of-technical-staff-research-post-training-modal-new-york-zgntyn07gfp2) — New York, NY
- [Member of Technical Staff - Research, Inference](https://feeny.ai/job/member-of-technical-staff-research-inference-modal-new-york-1a5bpnmmvvnx) — New York, NY
- [People Operations Generalist](https://feeny.ai/job/people-operations-generalist-modal-new-york-bf7tqrws58xr) — New York, NY
- [Systems Engineering Manager](https://feeny.ai/job/systems-engineering-manager-modal-stockholm-c0pw8s1byfbj) — Stockholm, Sweden