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Location: New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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. ABOUT THE ROLE: We’re looking for our first IT Lead to build and own the systems that enable everyone at Modal to work effectively and securely. You’ll own our employee technology environment end-to-end, including identity and access, devices, internal systems, SaaS applications, and day-to-day IT operations. You’ll work closely with Security and Engineering to build an environment that is secure by default, easy to operate, and scales with the company. This is initially a hands-on role. You’ll build systems, automate workflows, and solve problems directly. As Modal grows, you’ll define how the IT function should scale and eventually build a team around it. WHAT YOU’LL WORK ON: Identity & Access - Own employee identity and access across internal systems and SaaS applications - Build scalable onboarding, offboarding, and access lifecycle workflows - Improve SSO, MFA, least privilege, and access management in partnership with Security Devices & Endpoints - Own the lifecycle and security of employee devices - Build and maintain device management, configuration, patching, and endpoint security - Automate provisioning and make onboarding as close to zero-touch as possible Internal Systems & Automation - Own and improve the SaaS applications and internal systems we depend on - Build integrations and automate workflows across identity, HR, finance, and other business systems - Evaluate and deploy new internal capabilities, including AI tools and integrations - Use APIs, scripting, and internal tooling to solve problems that don’t fit neatly into off-the-shelf products IT Operations - Own employee support, hardware, asset management, procurement, and relevant vendor relationships - Build reliable, maintainable processes rather than scaling through manual work - Identify recurring problems and solve them at the system level Build the IT Function - Define the technical direction and operating model for IT at Modal - Establish the systems and processes we’ll need as the company grows - Determine when and where additional IT capacity is needed, and build the team over time WHAT WE’RE LOOKING FOR: - Experience owning IT or corporate technology in a fast-growing technology company - Strong understanding of identity, device management, SaaS administration, and endpoint security - Strong technical skills and comfort working with APIs, scripting, automation, and system integrations - Experience designing and automating employee lifecycle and access-management workflows - Good security judgment and experience working closely with Security and Engineering - Ability to independently identify problems, make pragmatic technical decisions, and drive them through implementation - Comfortable being hands-on today while building the systems and team needed as the company grows

240 000 – 290 000 $

Location: Stockholm 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collection over billions of objects. You'll work across the stack, from local disk and page cache to distributed blob storage and garbage collection and you'll help shape what storage becomes next as we push storage closer to workloads. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience building high-performance distributed storage or caching systems at a large scale (the more challenges you've worked through, the better) - Strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - Strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte-scale. - Prior experience with Rust KEY THINGS THE TEAM IS WORKING ON: - P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicating data across multiple blob storage providers - Automating garbage collection across hundreds of petabytes of data - Deploying colocated storage clusters to datacenters to accelerate high-throughput customer workloads

Location: New York; San Francisco Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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. ABOUT GTM ENGINEERING: GTM Engineering is responsible for the data, business logic, workflows, and agents that enable our Marketing and Sales teams to help customers get the most out of Modal. Like the infrastructure beneath the Magic Kingdom https://en.wikipedia.org/wiki/Disney_utilidor_system, much of our work happens behind the scenes. We build systems that anticipate and deliver what customers need to grow on Modal. We bring a product management, growth engineering, and data science approach to GTM, from centralizing our data platform https://deepline.com/blog/gtm-ai-nyc-chris-modal to building agents for account research https://parallel.ai/blog/case-study-modal. We're looking for a GTM Engineer to own our GTM data platform. This role combines analytics engineering with revenue operations: you'll build the org map, people graph, and data systems that help us discover future customers and support our GTM workflows, partnering closely with our Data team on the shared foundation. WHAT YOU'LL DO: - Build and maintain an org map and people graph connecting companies, labs, teams, and individuals to identify researchers, engineers, and early-stage startups, including people beyond our existing users and CRM. - Own identity resolution, enrichment, and CRM schemas so affiliations, roles, and relationships stay accurate, current, and traceable to their sources. - Build GTM data models in Snowflake and dbt connecting people, companies, workspaces, workloads, usage, and revenue, giving reps and agents a shared foundation for customer context. - Partner with RevOps and Marketing to define and implement metrics, data models, and business rules for routing, territory assignments, compensation, pipeline reporting, and attribution. - Partner with Data on usage forecasts and account signals; build reproducible reporting that reconciles actuals, forecasts, human adjustments, and credited attainment. - Build reverse ETL pipelines for ad audiences, lifecycle campaigns, CRM enrichment, outbound, and event outreach, preserving engagement history and campaign eligibility. - Own data quality and system health, from graph coverage and stale enrichment to failed syncs and historical reporting accuracy. - Build the tooling that helps GTM Engineering ship reliably, from development environments, automated tests, and deployments to backups and shared AI agents and skills. WHAT YOU SHOULD HAVE: - SQL fluency and Python proficiency. - You already use AI coding tools and agents to build, debug, and automate your work, and help teammates do the same. - Experience building data models and production pipelines with tools like Snowflake, dbt, Modal, or Hex. - Hands-on experience with CRM architecture, integrations, and revenue or marketing operations. - An understanding of how leads, accounts, opportunities, and revenue move through a business; experience with usage-based businesses is a plus. - High attention to detail and a habit of testing, documenting, and monitoring the systems you build.

Location: Stockholm 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We’re looking for strong engineers with experience building software that developers love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful abstractions that enhance developer productivity. REQUIREMENTS: - 5+ years of experience developing high-quality Python, JS or Go applications or libraries where the code is used or interacted with by other developers - A strong code-as-product sense that manifests as a focus on developer ergonomics and productivity. - Knowledge of async programming and concurrency management/pitfalls - A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. - Ability to participate in on-call rotation and respond to production incidents. - Ability to work in-person in our New York or Stockholm office. - Any of the following would be a plus: - Having built developer tools or SDKs - Experience maintaining open-source software - Good understanding of agentic development workflows - Familiarity with modern data / ML / AI tools and workflows KEY ACTIONS THE TEAM IS WORKING ON: - Improving developer and agent experience of our SDK and CLI - Developing new primitives to meet demand for entirely new areas that arise as a result of the ongoing industry transformation

150 000 – 350 000 $

Location: New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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. 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: Modal builds the infrastructure that lets engineers run AI workloads without the usual pain. To do this well, we need exceptional people – and that’s where you come in. As the first dedicated technical recruiter on our Talent team, you’ll own engineering and AI/ML searches end-to-end. You’ll work closely with our Head of Talent, founders, and technical leads to shape how we hire and help bring in the people who will define what Modal becomes. What you’ll do: - Run full-cycle recruiting for engineering and AI/ML roles (sourcing, pitching, guiding interviews, and closing candidates) - Partner with technical leaders to understand the real work and calibrate on what great looks like - Help set our technical hiring bar and how we evaluate talent - Execute creative top-of-funnel strategies that resonate with a strong community of talented, experienced engineers - Deliver a fast, respectful, honest candidate experience - Bring an equity lens to every stage of the process - Use data and market context to keep searches on track and expectations aligned - Support candidates as a trusted guide through high-stakes decisions REQUIREMENTS: - You know technical recruiting inside and out and enjoy the challenge of deeply technical roles - You’re curious – you ask the right questions and love understanding how things actually work - You influence with insight and honesty, not by simply having the loudest voice in the room - You move quickly and communicate clearly, even when things get messy - You’re a strong closer who builds trust early and stays ahead of concerns - You’re steady when priorities shift and can recalibrate without losing momentum - You care about people and want them to have a thoughtful, fair, and human experience throughout the process

Location: San Francisco; New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: Modal builds the infrastructure that lets engineers run AI workloads without the usual pain. To do this well, we need exceptional people – and that’s where you come in. As the first dedicated GTM recruiter on our Talent team, you’ll own sales, GTM, and other G&A searches end-to-end. You’ll work closely with our Head of Talent, founders, and GTM leads to shape how we hire and help bring in the people who will define what Modal becomes. What you’ll do: - Drive full-cycle recruiting for key hires across GTM and G&A functions (sourcing, pitching, guiding interviews, and closing candidates) - Partner with GTM leaders to understand the real work and calibrate on what great looks like - Help set our hiring bar and how we evaluate talent - Execute creative top-of-funnel strategies that resonate with a strong community of experienced GTM talent - Deliver a fast, respectful, honest candidate experience - Bring an equity lens to every stage of the process - Use data and market context to keep searches on track and expectations aligned - Support candidates as a trusted guide through high-stakes decisions REQUIREMENTS: - You know GTM recruiting inside and out and enjoy challenging searches - You’re curious – you ask the right questions and love understanding how things actually work - You influence with insight and honesty, not by simply having the loudest voice in the room - You move quickly and communicate clearly, even when things get messy - You’re a strong closer who builds trust early and stays ahead of concerns - You’re steady when priorities shift and can recalibrate without losing momentum - You care about people and want them to have a thoughtful, fair, and human experience throughout the process

Location: San Francisco Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems.Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated — whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA.We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. THE WORK: - Make container startup, checkpoint, and restore dramatically faster for large inference and training workloads. - Build multi-GPU and accelerator-aware snapshotting, including efficient handling of GPU memory and RDMA-enabled workloads. - Design zero-copy and low-copy data paths between container memory, filesystems, storage, and Modal’s runtime. - Optimize large snapshot pipelines using techniques such as parallel uploads, direct I/O, incremental snapshots, and more efficient memory handling. - Improve container image and filesystem performance across EROFS, FUSE, page caches, overlay filesystems, and remote storage. - Extend our sandboxed runtime to support new GPUs, drivers, profiling tools, and device capabilities across NVIDIA and AMD hardware. - Debug complex failures involving system calls, virtual memory, process lifecycle, kernel behavior, GPU drivers, and container isolation. - Safely roll out runtime and kernel changes across a heterogeneous fleet using compatibility controls, scheduling constraints, feature flags, and observability. - Work across the runtime, scheduler, storage, and GPU infrastructure—and take ambiguous production problems from investigation through deployment. WHAT WE’RE LOOKING FOR: - Strong Linux systems knowledge, particularly processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals. - Experience building or debugging container runtimes, sandboxes, Linux kernel, or similarly low-level infrastructure. - Strong programming ability in Rust, Go, or another systems language, with an interest in becoming productive in both Rust and Go. - Experience profiling and improving systems where memory movement, I/O, synchronization, or kernel interactions dominate performance. - Comfort debugging across abstraction boundaries, from application behavior down through runtimes, drivers, and the kernel. - An ability to turn loosely defined production problems into well-designed, reliable systems. - A desire to own important infrastructure and work closely with both internal teams and customers. RELEVANT EXPERIENCE: Any of the following would be helpful, but none is required: - gVisor, runsc, runc, OCI runtimes, seccomp, or checkpoint/restore systems. - Linux kernel development, virtualization, sandboxing, kernel modules, or device proxying. - CUDA, ROCm, GPU drivers, accelerator virtualization, or GPU profiling. - RDMA and high-performance networking. - FUSE, EROFS, direct I/O, mmap, page-cache behavior, or storage engines. - Large-memory or multi-GPU inference and training systems. - Contributions to open-source systems software. Prior gVisor or machine-learning experience is not required. We care more about strong systems fundamentals, curiosity, and the ability to learn unfamiliar parts of the stack. WHY THIS ROLE: The container runtime is directly on the critical path for inference performance. Improvements here can substantially reduce cold starts, increase token throughput, unlock new accelerator types, and make previously impractical workloads possible.This is an opportunity to work on unusually deep systems problems with immediate production impact. You’ll have room to shape the architecture, contribute to open-source runtime technology, and take ownership of foundational infrastructure used by every inference and training workload on Modal.

Location: New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We're looking for a Legal Operations Lead to join us as the first dedicated legal operations hire at Modal. You'll own the systems, records, and workflows that let a small legal team keep pace with a high-growth tech company — and you'll have an opportunity to build most of them from scratch. This is a great fit for a highly organized, systems-oriented operator who thrives in a fast-paced environment and wants to build operational foundations, not just maintain them. You'll report to our General Counsel and collaborate closely with the Finance, BizOps, GTM, and People teams. IN THIS ROLE, YOU WILL: - Build and maintain contract operations, including designing the contract lifecycle management workflows and approval logic, and continuing to iterate and improve those processes - Design legal intake process to support and route legal requests from internal stakeholders - Make the legal function faster with AI and build and configure tooling to make us more efficient - Manage corporate administration and record-keeping, including Board and stockholder matters, signature coordination, and building a knowledge management system and database - Be the point person for corporate compliance, including entity management and filings, including foreign and domestic qualifications and filings and coordinate with registered agents - Support stock administration and cap table hygiene - Manage outside counsel and legal spend REQUIREMENTS: - 5+ years in legal operations, contract operations, or a corporate paralegal role, preferably at a high-growth technology company - Demonstrated ability to build and document processes from the ground up, not just execute existing ones - Experience configuring workflows and templates within Ironclad or a similar CLM - Experience with AI tools, and good instincts about where they help and where they quietly introduce risk - Sound judgment about what to handle and what to escalate BONUS: - Exposure to corporate and equity administration; familiarity with Carta or a similar equity administration platform

Location: New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We're looking for a Senior Commercial Counsel to join us as the first commercial lawyer at Modal. This is a high-impact role for someone who wants to draft and negotiate a wide variety of commercial agreements and build the templates, playbooks, and positions that guide our operations. You'll report to our General Counsel and collaborate closely with the Sales, BizOps, Finance and Engineering teams and help build the foundation for a small but growing legal team. IN THIS ROLE, YOU WILL: - Own customer contracting, including MSAs, service orders, NDAs, DPAs, and BAAs - negotiating directly with customers and partnering with the Sales team throughout the full deal cycle - Lead vendor-side contracting, including capex procurement, SaaS tools, and consulting arrangements, among others - Build and maintain contract repositories, template libraries and contract playbooks - Partner with Legal operations on CLM management, including approval workflows and escalation logic - Review and revise operational policies, including terms of service, privacy policy, acceptable use, and website terms, and customer-facing marketing materials REQUIREMENTS: - We expect successful candidates will have approximately 5-10 years of combined law firm and in-house experience negotiating commercial technology agreements, with meaningful time supporting an enterprise sales motion - JD and active membership in good standing in New York or California - Deep familiarity with SaaS contracting - Extensive experience working within Ironclad or a similar CLM - Ability to build templates and playbooks from scratch - Working knowledge of privacy and regulatory data protection frameworks, such as GDPR and HIPAA - Sound commercial judgment: you know how to balance risk with the business needs of a high-growth tech company BONUS: - Experience with infrastructure, compute, or datacenter supply agreements

Location: San Francisco Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We're hiring a Field Marketing Manager in San Francisco to build and run the programs that turn Modal's target accounts into active customers. You'll work closely with our Sales team to plan regional campaigns, run events for the engineers and technical leaders we sell to, and report on how those programs contribute to pipeline and revenue. This is a hands-on role for someone who has run account-based field programs at a technical company and wants to help shape the function as it grows. WHAT YOU'LL DO: - Act as a strategic partner to Sales, aligning field programs with sales priorities and helping AEs create and accelerate pipeline in their territories. - Develop and execute account-based programs for named accounts, working with Sales to identify key stakeholders and the right mix of touchpoints for each. - Decide which industry conferences and sponsorships are worth investing in. Own what we bring, who we send, and whether we go back next year. - Plan and host high-touch 1:1 and 1:few events for prospects and customers, such as executive dinners, roundtables, and technical workshops, in partnership with AEs. - Own pre-event and post-event execution, including targeted invitations, meeting booking, and timely follow-up with Sales. - Build co-marketing programs with VCs, accelerators, and ecosystem partners to reach their portfolio companies and customers. - Track and report on program performance, including meetings booked, account engagement, and sourced and influenced pipeline, and use the results to plan future investment. - Own the VIP experience at Modal's flagship events, including our annual conference, Runtime. - Build repeatable processes and playbooks as the team grows. REQUIREMENTS: - A track record running field programs at a technical company. You can point to specific ones and clear outcomes. - You've worked directly with AEs and you're happy sharing a number with them. - Good judgment about where to spend. A lot of sponsorships look better than they perform, and you can tell which is which. Experience in AI or developer tools helps here. - Organized and self-directed. This role runs many events, partners, and vendors at once. - Experience producing events across a range of formats, from small executive dinners to large conference sponsorships and brand events. - Strong attention to detail and a high bar for taste and the quality of every event and touchpoint. - Comfort with data and reporting, including CRM, attribution, and pipeline analysis. - Familiarity with ABM, intent data, and marketing automation tools. - Experience building AI into marketing workflows, such as account research, audience development, event operations, and reporting. NICE-TO-HAVE: - Experience at an AI, developer tools, or cloud infrastructure company. - Experience marketing to technical audiences such as engineers, ML teams, and technical executives. - Experience bridging product-led and sales-assisted growth. - Existing relationships with Bay Area VCs, accelerators, or AI communities.

Location: New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We're looking for a hands-on Global Workplace Lead to own workplace experience across all Modal offices. You'll manage our Workplace Experience team and set the tone for the day-to-day operations, programs, and physical environments that make each location thrive. You care as much about how a space feels as how it functions, and bring the same taste and judgment to our offices that we bring to our product. You'll develop a deep understanding of what each office actually needs, and build trusted relationships with local leads and cross-functional partners across the organization. WHAT YOU’LL DO: - Manage and develop a team of workplace services professionals: setting direction, coaching performance, and building a high-functioning team. - Own operational quality across every office by tracking service levels and space utilization, spotting patterns, and fixing the underlying causes of recurring problems. - Stay ahead of what the business needs next by keeping a pulse on both local realities and company-wide priorities. - Build the global budget and vendor strategy for workplace experience, and hold contractors and service providers accountable to clear performance expectations. - Guide workplace experience through major transitions, including new office openings and relocations. - Shape how Modal's brand and culture show up physically — bringing the same clarity, craft, and attention to detail to our spaces that we bring to our product. - Synthesize data, stakeholder input, and business context into recommendations for continuous improvement. REQUIREMENTS: - 5+ years in workplace, facilities, or office operations, ideally at a high-growth tech company where you built programs rather than inherited them. - 2+ years of people management, including leading team members through office moves or openings. - Experience overseeing workplace operations across multiple offices, ideally in more than one country. - Strong taste and judgment — an instinct for what looks and feels like Modal. - A clear willingness to take a hands-on approach and dive into the details. - Demonstrated ability to influence cross-functional partners and translate company strategy into effective local execution. - The ability to thrive in a fast-paced workplace with rapidly changing priorities. - Excited to be in an in-office role, collaborating with team members IRL. - Willing and able to travel to Modal offices globally.

Location: New York; Stockholm; San Francisco Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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. ABOUT THE DATA TEAM: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: - Self-serve AI analytics tools (Hex, Snowflake) - Embedding with teams as a “data adviser”, providing strategic analysis and consulting WHAT YOU'LL DO: - Contribute to building the most modern analytics stack https://modal.com/blog/analytics-stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting - Influence work on new products like LLM Inference Endpoints https://modal.com/blog/qwen3-8-2-4t-a95b-now-available-on-modal through product analytics tracking - Identify millions of dollars of cost savings and optimization across our tools and financial operations - Write data pipelines that power the operations of our business, such as our cloud compute economics or sales comp - Create foundational datasets that can be used by people and AI tools to answer questions around product use cases, financial reporting, and marketing campaigns WHAT YOU SHOULD HAVE: - SQL fluency, Python proficiency - Professional experience with at least 2 of the following tools: Snowflake, dbt, dlt, Modal, Hex, Posthog - Ability to extend their work beyond just data reporting and into action and impact - High attention to detail - Excellent and precise communicator - Strong personability and relationship building skills NICE-TO-HAVE: - Experience with AI products, especially LLM inference and sandboxes - Experience in fin ops, fraud, sales ops, or risk, especially in the context of AI (e.g. token cost optimization) - Project management skills - Strong presence in the data community online and offline

Location: San Francisco; New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on top of it, whether that is a kernel panic, a broadcast storm during boot, or getting our container runtime to run on new architectures and platforms. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience operating fleets of physical hardware (bare metal provisioning, BMC/IPMI, PXE or network boot, firmware) or building the control planes that manage them (the more challenges you've worked through, the better) - Strong cloud skills - Strong knowledge of low-level operating system foundations (Linux kernel, drivers, networking, file systems, containers, etc.) - Effective at debugging across layers, from BGP flapping, Linux RPS, and vBIOS bugs to a Python control-plane service - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with GPUs and the NVIDIA software stack in production (drivers, health monitoring, XIDs, RDMA/NVLink) - Prior experience with Go KEY THINGS THE TEAM IS WORKING ON: - Automatic remediation of unhealthy machines (power cycling, reimaging, GPU recovery) to maximize uptime and minimize operator toil. - Automatic integration of new CPU, GPU, and storage servers into the fleet while managing hardware and network heterogeneity. - Network health monitoring and reliability across many datacenters, and standardization of bare metal network configuration. - Automatic hardware acceptance testing and benchmarking (CPU, disk, GPU, interconnect, network). - Custom network bootloader, machine image pipeline, and kernel and firmware management across the fleet.

Location: San Francisco; New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collection over billions of objects. You'll work across the stack, from local disk and page cache to distributed blob storage and garbage collection and you'll help shape what storage becomes next as we push storage closer to workloads. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience building high-performance distributed storage or caching systems at a large scale (the more challenges you've worked through, the better) - Strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - Strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte-scale. - Prior experience with Rust KEY THINGS THE TEAM IS WORKING ON: - P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicating data across multiple blob storage providers - Automating garbage collection across hundreds of petabytes of data - Deploying colocated storage clusters to datacenters to accelerate high-throughput customer workloads

Location: New York 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions. RESPONSIBILITIES: - Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features - Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team - Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality - Building and maintaining automated pipelines that will enforce the correctness of code examples and prose descriptions - Collaborating with engineers across the company to author documentation that is clear, consistent, and correct REQUIREMENTS: - 3+ years of experience in an engineering, product, or developer relations role, ideally in the devtools or infrastructure space - Experience authoring and/or editing high-quality technical content for developers - Knowledge of agentic engineering workflows and best practices - Comfort with modern software development practices (version control, CI/CD, testing)

Location: San Francisco; New York Workplace: Remote 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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. ABOUT THE ROLE: We're hiring the first Account Managers at Modal. You'll report to the Regional Director of Account Management and be a founding member of the team. This function does not exist yet. There is no playbook, no territory map, no established motion. You'll own a book of business from day one and build the motion at the same time — from fast-moving AI startups to large enterprise teams running critical infrastructure on Modal. This is a commercial role with a revenue target. You'll be measured on retention and expansion across your accounts. While you won't be delivering the technical recommendations and implementation, the work is technical by nature. Our customers are engineers running GPU workloads, inference, and batch jobs in production, and you need to hold your own in those conversations. The profile we're hiring is a technical account manager. You've worked at companies that are deeply technical and consumption in nature. You bring the commercial instincts to grow revenue from an existing base and enough technical depth to know which conversation actually matters. And you can credibly work with a CxO all the way down to a Developer. WHAT THE ROLE IS: - A founding seat. You're helping build the AM function with us, not joining one that already runs. The account plans, expansion motions, and customer cadence you and the rest of the founding team figure out are what we scale to every AM we hire after you. - A technical customer-facing role. You'll work directly with Developers and ML teams on what they're building and how Modal fits. You translate and triage the deeper technical work to FDEs and Product when it's needed. - A book of business. You’ll own a set of accounts and be responsible for the revenue that comes from them. Expect to be meeting with customers in your first few days because the best playbooks are built from real experiences. WHAT THE ROLE IS NOT: - A traditional post-sales role. You're measured on revenue, not health scores. - An on-call support function. You're not fixing bugs or triaging tickets. You're driving growth. - A technical delivery role. You're not implementing for the customer. You know where the technical work goes and you pull in the right people. - An inherited motion. Nothing is handed to you. If you identify gaps in process, tooling, or a playbook — you help build it. - A single-lane job. Our priorities go customer → company → team → me. We focus on delivering maximum impact vs. "this is my job". WHAT YOU'LL ACHIEVE: - Build Modal's account management function and iterate on it as we scale the business - Own and deliver on a revenue target across your book of accounts - Grow an account's first use case, expand into a second, and drive standardization across the Modal platform - Get fluent enough in Modal to hold your own with engineering teams on their workloads, and know when to pull in FDEs, Support, or Product - Work with Sales, Solutions Architects, FDEs, Support, and Product to grow accounts and feed customer signal back into the roadmap - Travel to customers as needed to support key accounts and drive expansion opportunities WHAT YOU'LL NEED TO BRING: - Customer-facing experience. You've owned a revenue target or supported a revenue target in a highly technical, consumption business. - Technical depth. You work autonomously with Developers through CxOs and understand the core parts of the developer tech stack. - AI builder. You're hands on building with AI tools — not just consuming workflows that were built for you. - Ownership. You run your book of business and projects like you're the CEO of it. You're highly organized bringing stability, predictability, and pace to your work. You take action vs. waiting for direction. - Learning velocity. You operate with the mindset of what I can do today vs. let me pick this up tomorrow. You move fast, take the learnings, and iterate on it. - Cross-functional partner. Low ego, easy to work with, and highly accountable. You ask for feedback, you act on it, and you'd rather be corrected early than right late. Internal teams love working with you. NICE-TO-HAVE: - Experience as a Technical Account Manager, Solutions Engineer, Solutions Consultant, or similar type role - Certification as an engineer (ex. Computer Science Degree, Professional Bootcamps) - Early GTM hire experience at a fast-growing startup - You've sat close to GPU spend, model training, or inference workloads

Location: San Francisco Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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: Modal's LLM inference platform delivers frontier performance https://modal.com/blog/kimi-k3-by-moonshot-now-available-on-modal for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots https://modal.com/blog/gpu-mem-snapshots and multi-cloud substrate https://modal.com/blog/resource-solver. We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area. This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, frontier inference serving, and performance optimization. RESPONSIBILITIES: Team - Recruit, hire, and grow a high-performing team of engineers; run regular 1:1s focused on coaching, feedback, and career growth. - Set clear performance expectations, hold a high bar, and build an environment where engineers do their best work. - Foster a culture of ownership, accountability, customer obsession, and continuous improvement. Technical and Product Direction - Drive technical and product decisions through design reviews, code reviews, and architectural discussions. - Lead our efforts working with customers with novel or frontier workloads so they can be successful running on Modal. - Translate learnings from frontier customers into a roadmap for our internal optimization platform and user-facing product, so that gains from optimization and research efforts are accessible to all of our users. - Establish standards for reliability and product excellence; ensure the team owns projects end-to-end, from spec through production. Cross-Functional Leadership - Partner with business operations and compute strategy on continuing to develop our strategy for compute purchases across a variety of accelerators. - Collaborate with GTM on product launches, positioning, and improving win rates for inference opportunities. - Help guide the roadmap for teams building the infrastructure platform underlying inference, as well as adjacent product teams. REQUIREMENTS: - 10+ years of industry experience, including 3+ years in a leadership role - Track record building high-performance systems at scale - Strong background in cloud infrastructure - Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.) - Nice to have: Experience working with LLM inference in production and familiarity with underlying concepts like engines, kernels, routing, KV cache management and speculative decoding.

Location: New York Workplace: OnSite 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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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. About Talent at Modal Modal is growing fast, and the programs that bring people in and set them up to succeed are still being built. You'll join the Talent team as one of its first hires focused purely on programs; working closely with recruiting and leadership to build the events, internship, and campus presence that shape how the best people discover and experience Modal for the first time. The Role As Talent Programs Manager, you will own Modal's talent events, our intern program, and our presence at career fairs, end-to-end. This is a build-from-the-ground-up role for someone who wants full ownership rather than an existing playbook to execute. You'll work directly with recruiters, hiring managers, and marketing to make sure every program ladders up to real hiring outcomes, and you'll be the person who makes candidates' and interns' first experience of Modal a great one. What You'll Do: - Own Modal's talent events strategy; meetups, recruiting mixers, tech talks, and community events, from concept through post-event follow-up - Design and run the intern program end to end: recruiting timeline, project scoping with hiring managers, mentorship matching, and conversion - Represent Modal at career fairs and campus events, and recruit and prep employee brand ambassadors to join you - Build and maintain relationships with university programs, bootcamps, and community organizations that feed our pipeline - Manage program budgets and vendor relationships; venues, swag, catering, event platforms - Track and report on program metrics: event pipeline conversion, intern conversion rate, cost per hire from programs - Move quickly without sacrificing the candidate or intern experience Requirements: - 3+ years running recruiting/talent programs, events, or university relations, with a track record of owning a program end-to-end including budget and vendors - High influence, low ego: you build relationships easily across recruiting, hiring managers, and marketing, and share credit freely - Strong project management skills; comfortable juggling multiple concurrent events and timelines without dropping details - Excellent written and verbal communication; comfortable representing Modal externally - Someone who takes ownership seriously: you drive programs to completion and build structures that let them scale - Based in or willing to relocate to NYC, in-office