Modal

Modal is seeking a foundational People Lead to establish and manage the people operations for our growing London office. This role is crucial for building the people infrastructure in the UK, ensuring a positive and supportive environment as the London team expands into a core hub. You will be the primary point of contact for all employee-related matters, from onboarding new hires to addressing daily concerns, and will own the end-to-end people operations for the UK, including systems, benefits, and compliance.

Modal is building the future of serverless computing, and the brand that carries that story is still taking shape. As a staff-level Brand Designer, you will have major influence over every brand surface, including the marketing website, campaigns, events, and editorial projects. You will join Modal's newly formed Brand team as one of its first senior hires, working directly with the Director of Brand Design and Head of Design to build a brand that developers recognize instantly and remember. As the studio grows, you'll help set its craft standard, guiding and mentoring earlier-career designers and shaping how the team critiques, ships, and shows work.

AI needs a new infrastructure layer, and Modal is building it. We are seeking a Detection & Response Engineer to develop systems for identifying, investigating, and responding to threats across our platform. This is an engineering role focused on automation, where you will build scalable detections, investigation tooling, and response capabilities, leveraging AI to enhance signal, investigation speed, and operational effectiveness. You will collaborate closely with infrastructure, platform, and security engineers to ensure every incident contributes to platform resilience.

Modal is building the next infrastructure layer for AI, enabling companies to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We are seeking a Revenue Operations Manager with a strong track record and a builder's mindset to join our in-person team in New York or SF. This high-impact, hands-on role involves owning the entire revenue operations function, from lead routing through deal closure and commission administration. You will collaborate closely with finance and sales leadership to establish the systems, dashboards, and processes necessary to scale our go-to-market strategy.

Modal is building the next infrastructure layer for AI, enabling category-defining companies to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We are seeking an experienced Enterprise Sales Manager to lead and scale our enterprise sales team. This role will drive strategic revenue growth through a consultative, customer-first approach, overseeing complex deal cycles, coaching Account Executives, and building the strategies necessary to win high-impact, multi-stakeholder deals in the rapidly evolving AI landscape.

AI needs a new infrastructure layer, and we're building it at Modal. Our customers include category-defining companies like Lovable, Ramp, Cognition, DoorDash, and Suno, who rely on Modal for instant GPU access, sub-second container starts, and native storage for tasks like low-latency inference, model fine-tuning, and accessing production-ready sandboxes at scale. We are seeking PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is ideal for candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and enhancing inference-time efficiency, reliability, and robustness in high-stakes real-world deployments.

We are building a platform that covers the entire lifecycle of Large Language Models (LLMs), from training to deployment and production observation. Our existing infrastructure supports multi-node training, elastic inference, sandboxes, and distributed volumes, with full control over the underlying systems. We are seeking individuals with deep research expertise in post-training techniques to complement our existing systems and product development efforts. This role is ideal for candidates passionate about improving current methods and creating novel techniques for large-scale model training, optimization, and inference. You will focus on extending models to handle long-context and long-horizon tasks, and enhancing inference-time efficiency, reliability, and robustness for critical real-world applications.

AI requires a new infrastructure layer, and Modal is building it. We provide customers with instant GPU access, sub-second container starts, and native storage, simplifying the deployment and serving of low-latency inference, model fine-tuning, and production-ready sandboxes at scale. We are seeking a Member of Technical Staff focused on Research and Inference to join our team. This role involves hands-on inference research, identifying high-impact areas, and driving them to completion. The primary focus will be on improving cost per token and tail latency for customer workloads.

AI needs a new infrastructure layer, and Modal is building it. We are seeking a People Operations Generalist to join our growing People team. This role will manage the entire employee lifecycle, from offer acceptance through offboarding, while also developing the processes and documentation necessary for our People function to scale with the business. This is an ideal opportunity for a highly organized, systems-oriented individual who excels in a fast-paced setting and is eager to establish operational foundations rather than simply maintain existing ones.

AI needs a new infrastructure layer, and Modal is building it. We are seeking an Engineering Manager to lead a group of highly experienced engineers. This is a hands-on leadership role where you will spend roughly half your time on technical contribution and half on people management. You will work closely with the team to set direction, remove blockers, and foster a strong engineering culture as they tackle complex systems challenges in distributed computing, large-scale data handling, and performance optimization. We are looking for an experienced engineering leader who thrives close to the work and enjoys building alongside their team when needed, earning trust through technical depth, communicating with clarity, and helping great engineers move fast and make sound decisions.

Modal is building the next infrastructure layer for AI, enabling instant GPU access, sub-second container starts, and native storage for companies to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. Having recently raised a significant Series C, the company is experiencing rapid growth and is looking for a Growth Engineer to own the technical foundation of its marketing and developer-facing web surfaces. This role is crucial for enhancing how users discover, understand, and engage with Modal's platform.

AI needs a new infrastructure layer, and this role is central to building it at Modal. We are seeking an Infrastructure Security Engineer to design and secure the core systems powering our platform. This position emphasizes building security directly into our infrastructure, covering aspects like container isolation, orchestration, identity, and secrets management within a multi-tenant, cloud-native environment. You will collaborate closely with engineering teams to establish secure primitives and ensure the platform's resilience, scalability, and trustworthiness by design. This is a hands-on, deeply technical role focused on practical implementation rather than compliance or policy.

AI needs a new infrastructure layer, and we're building it at Modal. We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you!

Modal is building the next-generation infrastructure layer for AI, enabling companies to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We are seeking a Compute Strategy and Operations Lead to manage the end-to-end procurement of GPU and CPU capacity. This role is critical as the compute secured directly impacts Modal's ability to sell and build its offerings. The ideal candidate will be responsible for anticipating infrastructure needs, sourcing supply from various providers, and negotiating contracts to ensure sufficient capacity.

We are seeking Forward Deployed ML Engineers to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you will partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads, including LLM serving, model training (SFT, RLHF), audio pipelines, and scientific computing. You will help teams reach outcomes that many engineers cannot achieve on their own. The FDE team comprises world-class software engineers, computational scientists, ML engineers, and former founders, and we are looking for individuals with strong engineering fundamentals, deep curiosity across the AI stack, and energy for tackling hard problems directly with customers.

We are seeking Forward Deployed ML Engineers to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you will partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads, including LLM serving, model training (SFT, RLHF), audio pipelines, and scientific computing. You will help teams reach outcomes that many engineers cannot achieve on their own. The FDE team comprises world-class software engineers, computational scientists, ML engineers, and former founders, and we are looking for individuals with strong engineering fundamentals, deep curiosity across the AI stack, and energy for tackling hard problems directly with customers.

Modal is seeking a high-impact Solutions Architect to lead technical strategy for its most strategic enterprise accounts. In this role, you will act as the executive technical counterpart to Enterprise Account Executives, guiding complex evaluations, shaping infrastructure modernization roadmaps, and promoting multi-product adoption for AI/ML workloads. This is a strategic, consultative position that requires deep architectural knowledge, executive presence, and the ability to influence significant infrastructure decisions. You will collaborate directly with CTOs, VPs of Engineering, and ML platform leaders to reimagine how AI infrastructure is built and operated. If you excel in fast-paced technical sales environments and are passionate about shaping the infrastructure powering modern AI companies, this role is for you.

Modal is building the next-generation infrastructure layer for AI, enabling instant GPU access, sub-second container starts, and native storage for customers like Lovable, Ramp, Cognition, DoorDash, and Suno. We are seeking an Engineering Manager to lead a team of experienced engineers focused on our serverless GPU platform. This is a hands-on leadership role where you will balance technical contributions with people management, setting direction, removing obstacles, and cultivating a strong engineering culture while addressing complex challenges in distributed computing, large-scale data handling, and performance optimization.

AI needs a new infrastructure layer, and Modal is building it. We are seeking business operations managers to join our team and work closely with marketing, sales, operations, and finance across a variety of initiatives to help scale the business in its next phase of growth. This role is for a generalist who will get involved in all the business and operational aspects of a high-growth startup.

AI needs a new infrastructure layer, and Modal is building it. We provide instant GPU access, sub-second container starts, and native storage, enabling customers to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. As a rapidly growing cloud infrastructure company, we are seeking to dramatically improve our platform's reliability while scaling our team and customer base. This role is ideal for individuals with deep systems thinking, a passion for reliability, and a drive to enable others to move faster at scale.