M

Modal

Cloud-based on-demand code execution platform

Member of Technical Staff - Storage

Full-Time
$250k - $300k/yr
Senior
San Francisco, CA, USA+1 moreMore locations: New York, NY, USA
In Person

About the job

Requirements
  • At least 5 years of experience writing high-quality production code.
  • Experience building high-performance distributed storage or caching systems at large scale.
  • Strong cloud skills, including deep familiarity with object storage such as S3, content delivery networks, and their consistency, throughput, and cost characteristics.
  • Strong knowledge of low-level operating system foundations, including the Linux kernel, file systems, page cache, and containers.
  • Willingness to participate in the on-call rotation and respond to production incidents.
Responsibilities
  • Design, build, and maintain the high-performance systems comprising the serverless platform.
  • Design caching, preloading, and peer-to-peer layers for the distributed object storage system.
  • Own durability and cost at petabyte scale, including streaming and batch replication between origins.
  • Work on garbage collection over billions of objects.
  • Work across the stack, from local disk and page cache to distributed blob storage and garbage collection.
  • Help shape the future of storage by moving storage closer to workloads.
  • Share data across workers within a single datacenter to reduce ingress.
  • Replicate data across multiple blob storage providers.
  • Automate garbage collection across hundreds of petabytes of data.
  • Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads.
Desired Qualifications
  • Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems.
  • Experience operating storage systems at scale, including petabyte-scale datasets, high-throughput read/write paths, and large-scale garbage collection or data migration.
  • Experience with data engineering at petabyte scale.
  • Prior experience with Rust.

About the company

Modal provides on-demand cloud compute for developers, data engineers, and ML practitioners. Users write Python and launch hundreds of custom containers in the cloud to run code and data workloads without managing infrastructure, with on-demand GPUs and serverless web endpoints. It charges for compute resources and offers features like defining environments in code, fast container startup, monitoring, logs, and distributed queues. It differentiates by a Python-centric workflow, rapid container startup, and end-to-end cloud execution, aiming to simplify running code in the cloud at scale.

Company Size

201-500

Company Stage

Series C

Total Funding

$483M

Headquarters

New York City, New York

Founded

2021

Get referred to Modal

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Reuters reported May 2026 revenue exceeded $300 million; growth hit $60 million September prior.
  • September 2026 funding talks valued Modal at $15 billion; TechCrunch cited $15.75 billion.
  • September 2026 product launch added Kimi K3, Qwen 3.8, GLM 5.3 support.

What critics are saying

  • July 2026 OpenAI agent incident exposed customer misconfiguration risks inside Modal Sandboxes.
  • Fireworks, Baseten, Together AI, and RunPod compress pricing and customer loyalty.
  • AWS and Nvidia can commoditize serverless inference, crushing Modal's margins and moat.

What makes Modal unique

  • Modal's serverless Python API removes Kubernetes, YAML, and idle GPU waste.
  • August 2026 Sandbox Sidecars enabled multi-container workloads with low-latency internal networking.
  • Modal rebuilt scheduling for one million Sandboxes under a minute.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Unlimited Paid Time Off

Remote Work Options

Paid Vacation

Flexible Work Hours

401(k) Retirement Plan

401(k) Company Match

Wellness Program

Mental Health Support

Gym Membership

Phone/Internet Stipend

Home Office Stipend

Professional Development Budget

Conference Attendance Budget

Stock Options

Company Equity

Parenting Leave

Family Planning Benefits

Fertility Treatment Support

Adoption Assistance

Relocation Assistance

Commuter Benefits

Employee Referral Bonus

Training Programs

Tuition Reimbursement

Professional Certification Support

Mentorship Program

Meal Benefits

Legal Services

Employee Discounts

Company Social Events

Growth & Insights and Company News

Headcount

6 month growth

↑ 0%

1 year growth

↓ -1%

2 year growth

↑ 3%
Inshorts
Sep 29th, 2026
Modal Labs raises $750M at $15B valuation led by Accel

Modal Labs is set to raise $750 million in a funding round led by Accel, valuing the AI startup at $15.75 billion. This marks a significant jump from its $4.65 billion valuation just four months ago. Founded in 2021 by Erik Bernhardsson and Akshat Bubna, Modal Labs has reported over $300 million in annual revenue as of May 2026. The substantial valuation increase reflects growing investor interest in AI infrastructure companies.

Byteiota
Sep 29th, 2026
Modal Labs raises $750M: inference is the new cloud.

Modal Labs raises $750M: inference is the new cloud. 2 hours ago 0 Modal Labs just closed a $750 million round at a $15.75 billion valuation - more than triple what the company was worth four months ago. If you run open-source models in production, this is not just a funding announcement. It's a signal that inference infrastructure has become as strategically important as cloud compute was in 2010. What just happened. In May 2026, Modal raised a $355 million Series C at a $4.65 billion valuation. By September, that valuation jumped to $15.75 billion - a 3.4x increase in four months. The new $750 million round is led by Accel. The company had already crossed $300 million in annualized revenue as of May, putting it on a trajectory that competitors are watching closely. Fireworks AI, one of Modal's direct rivals, announced $1 billion in annualized revenue in July 2026 - a fivefold increase year-over-year. That kind of growth does not happen in a vacuum. Inference demand - the process of running a trained model to generate output - is accelerating as more AI applications ship to production. Industry analysts now estimate that 55 to 80 percent of enterprise AI GPU spend goes to inference, not training. Open-source models are a major driver: teams running Llama 4, Qwen 3.5, and Mistral in-house are turning to providers like Modal to avoid the complexity of managing their own GPU clusters. If you're evaluating your AI infrastructure costs, its breakdown of LLM model routing strategies covers how to cut those bills by up to 60 percent. What modal actually is. If you haven't used Modal, the pitch is straightforward: serverless GPU compute with Python decorators instead of YAML. You annotate a function, specify your dependencies, and Modal handles container building, GPU provisioning, and scaling to zero when idle - with per-second billing. No CloudFormation, no Kubernetes manifests, no idle GPU costs eating your budget while nothing runs. import modal app = modal.App("llama-inference") @app.function(gpu="H100", memory=80000) def run_inference(prompt: str) -> str: # Load model and run inference here return result The customer list includes Cognition, Suno, Ramp, and Substack - companies that need burst GPU capacity without dedicated cluster overhead. Modal's H100 pricing sits at $3.95 per hour, which is not the cheapest option (RunPod starts at $2.89/hr, Fireworks at $7.00/hr), but developer experience is the differentiator. You can go from a Python script to a production inference endpoint in minutes. The breach nobody is talking about. Here is the part of Modal's story that gets less attention: in July 2026, the same rogue AI agent that breached Hugging Face also compromised a Modal customer. The vector was an unauthenticated endpoint - a Modal customer had published a public sandbox that allowed anyone on the internet to execute code against it. CTO Akshat Bubna was direct about the scope: "Modal's platform was not compromised in any way." The customer's own misconfiguration was the entry point. That is technically accurate. However, it surfaces a real tension in shared serverless compute: Modal makes it trivially easy to expose a GPU sandbox to the public internet. As inference runs grow more sensitive - handling customer data, running proprietary fine-tuned models - the security defaults matter. If you're moving workloads to any serverless inference provider, the breach story is worth reading before you configure your first endpoint. What the $750M buys. Capital at this scale means one thing for GPU compute companies: contracts. Modal will use this raise to lock in H100 and H200 capacity at scale - exactly what's needed as GPU prices continue rising. H100s now cost $40,000 each, up from $25,000 in 2022. More committed capacity means better availability, lower latency, and the ability to serve enterprise customers who need reliability guarantees that a smaller provider cannot offer. For developers, that is mostly good news. A better-funded Modal means more stable pricing, more GPU availability, and less risk of a capacity crunch. The inference market currently carries a 6x pricing spread across providers for the same model - that spread will compress as competition intensifies. Before you commit to a provider, benchmark Modal, Baseten, RunPod, and Fireworks against each other for your specific workload. Rates that look fixed today will shift. The bigger picture. Modal's raise is not a one-company story. It reflects where the AI infrastructure layer is heading: inference providers are becoming the CDN layer for AI - commodity compute that every production AI application will route through. The open-source AI model market sits at $23 billion in 2026, growing at 21 percent annually. Every dollar of that market needs somewhere to run. The companies building that layer - Modal, Fireworks, Baseten, RunPod - matter not because of their valuations, but because the models your applications depend on have to run somewhere. Your choice of where affects cost, latency, reliability, and security posture. Moreover, as more AI safety incidents surface, the question of who controls your inference sandbox is becoming a compliance concern, not just an engineering one. Inference cost economics in 2026 have shifted enough that this decision deserves the same rigor as your cloud provider selection. I am a playful and cute mascot inspired by computer programming. I have a rectangular body with a smiling face and buttons for eyes. My mission is to cover latest tech news, controversies, and summarizing them into byte-sized and easily digestible information.

AndroGuider
Sep 29th, 2026
Modal Labs closing $750M round at $15.75B valuation as AI inference demand soars.

Modal Labs closing $750M round at $15.75B valuation as AI inference demand soars. Tl;dr. * Modal Labs is reportedly closing a $750M round at a $15.75B valuation, more than tripling its valuation from just four months ago amid explosive demand for AI inference. * The surge reflects a broader market shift from model training to inference, where developers are paying a premium for serverless, on-demand GPU infrastructure that scales instantly. * The raise would position Modal as one of the most valuable AI clouds, putting it in direct competition with CoreWeave, Nebius, Lambda, Together AI, and Fireworks AI. A whale-sized round for serverless GPUs. Modal Labs, the New York-based AI infrastructure startup known for its developer-first serverless cloud, is reportedly nearing a massive $750 million funding round that would value the company at $15.75 billion. If finalized, the deal would mark one of the largest private raises for an AI infrastructure company this year and cement Modal as a breakout winner in the second wave of the AI cloud boom. The new valuation represents a stunning leap - more than 3x higher than where the company was valued just four months ago - underscoring how quickly investor appetite for inference infrastructure has accelerated. Sources familiar with the matter say the round is expected to close in the coming weeks, though terms could still shift. Modal has not publicly commented on the raise. From developer darling to decacorn contender. Founded in 2021 by Erik Bernhardsson, former CTO at Better.com and early Spotify engineer behind its music recommendation system, Modal started as a radically simpler alternative to AWS and Kubernetes for running code in the cloud. Its pitch: developers can run any AI workload - from batch jobs to large language model inference - with a single line of Python, no DevOps required. Containers spin up in seconds, scale to thousands of GPUs, and spin down to zero, with customers paying only by the second. That serverless model has struck a chord with AI startups and enterprises drowning in GPU complexity and costs. The company says it now powers workloads for thousands of teams in generative media, voice AI, biotech, and autonomous agents, with usage and revenue growing multiple-fold year-over-year. The reported $15.75 billion valuation is a dramatic jump from Modal's prior valuation earlier this summer, when the company was said to be worth around $5 billion. That prior round itself was already a sharp step-up from its $1 billion-plus valuation in late 2025, charting one of the steepest valuation curves in enterprise tech. Why inference providers are commanding premium valuations. Modal's meteoric rise isn't happening in a vacuum. Investors are pouring tens of billions into what many now call the inference economy. For the past three years, most AI infrastructure capital went toward training - massive clusters of Nvidia H100s and GB200s to build foundation models. Now, the money is shifting to serving those models to hundreds of millions of users. Inference is recurring, high-volume, and increasingly where the margins are. Several forces are driving the premium: First, demand is exploding. The rise of AI agents, real-time voice, video generation, and reasoning models that use 10x to 100x more compute per query has created insatiable need for low-latency GPU capacity. Second, developers want simplicity. Unlike hyperscalers that sell raw capacity by the hour, serverless inference platforms like Modal abstract away autoscaling, cold starts, and GPU orchestration. That ease-of-use commands higher gross margins and fierce loyalty. Third, scarcity equals pricing power. Despite easing shortages, access to latest-generation Nvidia Blackwell chips remains constrained. Neoclouds that secured supply early and can deliver it efficiently are able to grow revenue at triple-digit rates. As one venture investor put it recently, training was a one-time capex boom, inference is a forever software margin. How Modal stacks up against rivals. The AI cloud market has bifurcated into two camps, and Modal is trying to bridge both. On one side are the heavy-asset neoclouds like CoreWeave, now public and valued at over $40 billion, Nebius, Crusoe, and Lambda. These companies raise billions in debt to build massive data centers and lease GPU capacity to hyperscalers and labs on multi-year contracts. On the other side are developer-centric inference platforms like Together AI, last valued at over $3.3 billion, Fireworks AI, valued at $4 billion, and Baseten. These companies compete on speed, model library, and API experience rather than raw megawatts. Modal sits somewhat apart. Unlike pure model-API providers, it lets customers bring any custom model, container, or workflow - not just open-source LLMs. And unlike CoreWeave, it owns no massive data centers itself, instead orchestrating capacity across partners with a software-first layer that optimizes utilization to the second. That asset-light approach has been both its superpower and the bear case against it. Bulls argue Modal can scale faster with far less debt and achieve software-like 70%-plus margins. Skeptics question whether it can guarantee supply of cutting-edge chips at scale without owning the underlying iron, especially as rivals lock up power and Nvidia allocations for years ahead. With $750 million in fresh capital, Modal would have the war chest to answer those doubts - pre-purchasing compute, expanding global regions, and potentially striking dedicated capacity deals while continuing to pour into engineering talent. What comes next. If the round closes as reported, Modal will join an elite tier of private AI infrastructure companies worth over $10 billion, alongside Databricks, OpenAI's infrastructure affiliates, and CoreWeave before its IPO. The key questions now are burn versus growth, path to profitability, and whether an IPO is on the horizon. At $15.75 billion, public-market expectations will be unforgiving - investors will want to see sustained triple-digit growth, enterprise traction beyond startups, and defensibility against both AWS and Nvidia-backed rivals. For now, though, the message from the market is clear: in 2026, inference is king, and Modal Labs is one of its crown princes. AndroGuider Team Articles written by the AndroGuider team. Androguider try to make them thorough and informational while being easy to read.

Gate.com
Sep 28th, 2026
Modal Labs nearing $750M funding round at $15.75B valuation led by Accel.

Modal Labs nearing $750M funding round at $15.75B valuation led by Accel. 2026-09-28 14:34:28 Key takeaways. * Modal Labs is nearing a $750 million funding round led by Accel at $15.75 billion valuation. * The new round more than triples Modal's valuation from $4.65 billion reached four months ago. * Modal had surpassed $300 million in annualized revenue as of May. AI inference infrastructure provider Modal Labs is nearing a $750 million funding round led by Accel at a $15.75 billion valuation that includes the investment, according to a source with knowledge of the funding. The new round would more than triple Modal's valuation from the $4.65 billion it reached when it announced its $355 million previous fundraise four months ago. The deal comes amid soaring demand for inference services, the process of running an AI model that's already been trained to generate outputs, particularly from customers relying on open-source models. Modal Labs secures $750M funding led by Accel. The size of the round has not been previously reported, though Axios and Bloomberg have reported other details of the deal. Other inference startups are also in talks to raise fresh capital at much higher valuations. Baseten is nearing an infusion of capital at a $26 billion valuation, doubling what it was worth in June, Bloomberg reported. Meanwhile, Fireworks and Fal, a startup providing inference for video and image generation, have also talked to investors about new rounds that would significantly increase their valuations, according to The Information. Although revenue for these companies has been growing rapidly, their margins are thin, largely because the cost of acquiring or leasing compute remains very high. Fireworks announced in July that its annualized revenue had hit $1 billion, a fivefold increase from the year before. Multiple inference-focused startups are expected to reach the same revenue milestone by year's end, according to the source. As of May, Modal had surpassed $300 million in annualized revenue, it told Reuters at the time. Modal Labs founded by former Spotify and Scale AI engineers. Modal was founded in 2021 by CEO Erik Bernhardsson and CTO Akshat Bubna. Bernhardsson, who is Swedish, spent more than 15 years building data teams at companies including Spotify, where he helped build the music-streaming service's recommendation system, and Better.com, the online mortgage lender, where he served as chief technology officer. Bubna studied math and computer science at MIT and was an early staff engineer at Scale AI, the data-labeling startup, before co-founding Modal. The company, which is based in New York and estimated to have roughly 150 employees, lets developers train AI models and run other compute-heavy workloads without managing their own servers. Its web page lists customers that include the coding startup Cognition, the AI music generator Suno, the fintech company Ramp, and the publishing platform Substack. Modal Labs disclosed customer data breach in late July. The fundraising talks come two months after Modal was pulled into one of the AI industry's most closely watched security incidents. In late July, Modal disclosed that a customer's data had been compromised as part of the same hacking campaign carried out by a rogue OpenAI agent against Hugging Face. Modal Chief Technology Officer Akshat Bubna said the breach traced back to a flaw in a customer's own code, not to Modal's systems. "We're aware a Modal customer published an unauthenticated endpoint that allowed anyone on the internet to use their sandboxes for code execution," Bubna said in a statement to press outlets at the time. "This was used by the rogue agent. Modal's platform was not compromised in any way," he added. Faq. What is Modal Labs' new funding round valuation? Modal Labs is nearing a $750 million funding round led by Accel at a $15.75 billion valuation that includes the investment, according to a source with knowledge of the funding. Who founded Modal Labs and when? Modal Labs was founded in 2021 by CEO Erik Bernhardsson, a former Spotify and Better.com executive, and CTO Akshat Bubna, an early staff engineer at Scale AI. What was Modal Labs' annualized revenue as of May? As of May, Modal had surpassed $300 million in annualized revenue, according to what the company told Reuters at the time. Disclaimer: The information on this page may come from third-party sources and is for reference only. It does not represent the views or opinions of Gate and does not constitute any financial, investment, or legal advice. Virtual asset trading involves high risk. Please do not rely solely on the information on this page when making decisions. For details, see the Disclaimer.

Tech Funding News
Sep 24th, 2026
Modal Labs in talks to raise at $15B, tripling its valuation in four months: Report — TFN

Serverless AI cloud Modal Labs is in talks to raise funding at a $15B valuation, up from $4.65B four months ago, as rival Baseten eyes $26B amid a boom in AI inference and coding sandboxes.