Customer Engineer

Modal modal.com Open · verified Sep 24, 2026

New York London or StockholmSan Francisco Full-time Mid-level Solutions & Sales Engineering

At a glance

Mid-level Solutions & Sales Engineering role at Modal. New York · full-time · $150,000–$220,000 base.

SalaryStated by Modal

$150,000 – $220,000

Base salary for this role, in USD per year, as published in the posting.

RoleSolutions & Sales Engineering

SeniorityMid-level

LocationNew York

EmploymentFull-time

Base pay$150,000–$220,000

PostedSep 23, 2025 · 12mo ago

Also hiring inLondon or Stockholm, San Francisco

Role brief

Growth Roles summary, based on the employer's posting.

What you'll do

Ship production fixes, features, and automation that improve Modal for all users
Help developers and ML engineers debug, tune, and design workloads across Slack, email, and calls
Build tooling, dashboards, and automated workflows that make customer support scale
Turn recurring customer issues into documentation, API, and feature improvements
Create examples, demos, and technical content while contributing to open source

What you bring

Deep expertise in low-level infrastructure or ML/AI, plus working knowledge of the other area
Experience with operating systems, file systems, networking, profiling, clusters, or distributed systems
Hands-on work training models, optimizing inference, using GPUs, or building ML infrastructure
An engineering approach that replaces repetitive manual work with automation
The ability to explain technical issues, write clear bug reports and documentation, and collaborate internally

Who this fits

You’ll suit this role if you want an engineering position that combines direct customer work with production coding. Your work will be guided by customer problems, with time split roughly between helping users and improving the platform. The role is full-time in New York and centers on deep AI/ML or low-level systems work.

From the employer

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,Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

The Role:

We're looking for engineers with deep AI/ML and low-level systems experience who want to build the best technical support experience in the world. This isn't a traditional support role — it's an engineering role where you happen to be closest to our customers.

You'll split your time roughly 50/50 between working directly with customers and shipping fixes, features, and automation that improve Modal for everyone. When you help a customer debug a training run, you'll also fix the underlying issue in the platform. When you notice ten customers hitting the same friction point, you'll build the tooling or automation that eliminates it entirely.

This role is for people who solve problems, not people who answer tickets. The problems you encounter are deeply technical and arise from running some of the most demanding AI workloads in the world. You'll be a member of our engineering team, contributing production code alongside the engineers building the core platform. The difference is that your roadmap is shaped by what you learn at the frontier of customer experience. You will:

Ship code that matters. Fix bugs, build features, and create automation that improves the experience for every Modal user — not just the one who reported the issue.
Work directly with customers. Help developers and ML engineers debug, optimize, and architect their workloads across Slack, email, and calls.
Build scalable systems. Design tooling, dashboards, and automated workflows that make support efficient at scale — delighting customers at the most important moments.
Close the feedback loop. Translate patterns you see in the field into concrete improvements — docs fixes, API changes, or new feature proposals.
Contribute to open source and technical content. Write examples, build demos, and publish content that helps the broader community succeed on Modal.

Requirements:

Accomplished in key areas. You bring depth in either low-level infrastructure or ML/AI, and you're not lost in the other.
Low-level infrastructure experience. Operating systems, file systems, networking, performance profiling, cluster management and distributed systems.
AI/ML engineering experience. Training models, optimizing inference, working with GPUs, or building ML infrastructure.
Automation mindset. Your instinct when you see a manual process is to eliminate it and you have the engineering background to make that happen.
Clear communicator. Can explain a systems issue to a customer, write a crisp bug report, and draft documentation, all while collaborating internally to ship improvements.