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Location: London 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: In short, the People Operations Generalist for the UK will own day-to-day People Operations for our growing UK team. Reporting to our People Lead, Europe, you'll be the go-to person for UK employees and managers, with ownership across the employee lifecycle - from onboarding and payroll coordination to employee changes and offboarding. You'll bring strong UK People Operations expertise, help build scalable processes, and partner with the broader People team on global programs. You'll also help run the day-to-day London office and work closely with Recruiting on the final stages of the UK candidate experience, including onsite interview coordination and candidate support. Things move fast at Modal, and priorities change as we grow. We're looking for someone flexible and hands-on who’s happy to jump in, figure things out, and take on whatever needs doing across their area. Some of the things you'll do: - Own day-to-day People Operations for our UK employees, including onboarding, employee changes, leave, documentation, and offboarding. - Act as the first point of contact for UK employees and managers, escalating more complex matters as needed. - Partner with payroll, benefits, pension, and other external providers to ensure smooth UK administration. - Keep employee data, documentation, and People processes accurate, compliant, and up to date. - Build and improve UK People processes, policies, and self-service resources as we scale. - Execute global People programs locally, ensuring they work effectively for our UK team. - Own day-to-day office operations in London, collaborating with internal partners (like the Workplace team!) and third party vendors. - Coordinate onsite interviews and the final stages of the candidate experience for UK hires. - Plan and support local employee events and initiatives. WHAT WE'RE LOOKING FOR: - 5+ years of People Operations or HR experience, ideally with experience at multiple fast-growing companies at a similar stage of growth. - Strong knowledge of UK People Operations and employment practices, including payroll, benefits, pensions, and employee lifecycle processes. - Comfortable working independently and taking ownership, with the judgment to know when to escalate or bring in additional expertise. - Highly organized and detail-oriented, comfortably managing multiple priorities in a fast-moving environment. - Strong written and verbal communication skills, with a high level of discretion when handling sensitive employee matters. - A hands-on, flexible approach; you’re comfortable figuring things out, building processes from scratch, and jumping into whatever needs doing. - Experience with office operations, workplace, or recruiting coordination is a plus. - Based in London and comfortable working from the office five days a week (life happens, of course!)

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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. ABOUT MODAL DESIGN: Modal is building the future of serverless computing, and the brand that carries that story is still taking shape — You'll join Modal's newly formed Brand team inside our design org as one of its first senior hires, working directly with the Director of Brand Design and Head of Design to build a brand developers recognize instantly and remember. THE ROLE: As a staff-level Brand Designer, you will have major influence over every brand surface: the marketing website, campaigns, events, editorial projects like the GPU Glossary https://modal.com/gpu-glossary and forthcoming publications, and out-of-home work as we scale into larger formats. You'll also be a beacon to external agencies, representing Modal's internal creative voice and making sure the work translates into a system we can actually build on. And as the studio grows, you'll help set its craft standard — guiding and mentoring earlier-career designers and shaping how we critique, ship, and show work. WHAT YOU'LL DO: - Define and evolve Modal's visual identity across web, marketing, campaigns, and editorial — building a cohesive, distinctive system rather than one-off assets - Lead concept and execution for brand campaigns across digital and out-of-home, from paid social to large-format outdoor, ensuring the work is consistent, distinctive, and built to perform - Own branded experiences for events and GTM: environments, collateral, swag, and conference presence that feel unmistakably Modal - Help codify the brand as it matures: design language, principles, and the rules that hold it together - Mentor and critique the work of other designers, helping the studio's output stay coherent and ambitious as it scales - Move quickly without sacrificing quality REQUIREMENTS: - 7+ years of brand design experience, building brands for technically complex products — developer tools, infrastructure, or AI. You know how to make something deeply technical feel compelling and clear. - High influence, Low ego: You work well with others, share credit freely, and act as force for positivity within the brand team - A portfolio that demonstrates exceptional typography, color, composition, and a recognizable point of view - Experience designing brand systems that extend from identity to motion to web – the more the better - Ability to interpret and contribute to brand strategy - Someone who takes ownership seriously: you drive work to completion, raise the quality bar, and build structures that let others do the same - Strong taste, and the ability to defend it. Has opinions, backs them up, takes feedback well

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: We're looking for a Detection & Response Engineer to build the systems that help us identify, investigate, and respond to threats across our platform. This is an engineering role focused on automation. You'll build detections, investigation tooling, and response capabilities that scale with our infrastructure, using AI where it meaningfully improves signal, investigation speed, and operational effectiveness. You'll work closely with infrastructure, platform, and security engineers to ensure every incident makes the platform more resilient. WHAT YOU'LL WORK ON: DETECTION ENGINEERING - Design and build high-fidelity detections for attacks, abuse, and anomalous behavior across our infrastructure and production systems - Continuously improve detections based on telemetry, threat intelligence, and lessons learned from incidents - Improve visibility across cloud infrastructure, containers, identity systems, and production services INCIDENT RESPONSE - Lead or participate in investigations spanning production infrastructure, cloud environments, and internal systems - Build playbooks and automation that reduce investigation time and improve response consistency - Drive post-incident improvements that eliminate entire classes of future incidents SECURITY TOOLING & AUTOMATION - Build internal tooling that improves detection, investigation, and response workflows - Leverage LLMs to automate repetitive analysis, accelerate investigations, and surface actionable insights from security telemetry - Improve the collection, quality, and usability of security telemetry across the platform ENGINEERING PARTNERSHIP - Partner with engineering teams to ensure new systems are observable and secure by default - Help teams instrument services with the telemetry needed for effective detection and response - Drive security improvements that make the platform easier to defend over time WHAT WE'RE LOOKING FOR: - Experience in detection engineering, incident response, security engineering, or software engineering with a strong security focus - Strong software engineering skills with experience building production systems - Experience investigating security incidents in cloud-native or distributed environments - Familiarity with modern cloud infrastructure, Kubernetes, Linux, and networking - Experience building detections using logs, telemetry, behavioral signals, or large-scale event data - Strong SQL skills for investigating security events and developing detections - Interest in applying AI and LLMs to detection, investigation, and response, including understanding emerging threats involving AI-powered systems - Strong written and verbal communication skills PREFERRED QUALIFICATIONS: - Experience building AI- or LLM-powered security tooling - Experience with SIEM, SOAR, or EDR platforms - Experience with Kubernetes security or large-scale cloud infrastructure - Experience with threat hunting, malware analysis, or digital forensics - Experience contributing to security operations in a high-growth engineering organization

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're seeking a Revenue Operations Manager with a strong track record, a builder's mindset, and a bias for action to join our in-person team in New York or SF. This is a high-impact, hands-on role. You'll own the entire revenue operations function, from top-of-funnel lead routing through deal close and commission administration. You'll work closely with our Head of Finance & People Ops and sales leadership to build the systems, dashboards, and processes that scale our go-to-market motion. WHAT YOU'LL DO: - Own the lead routing process from inbound and partnering with marketing to ensure proper attribution - Run effective territory management & strategy for Geo based decisioning - Support & strategise every aspect of revenue operations in your territory - Own the strategy for capacity forecasting, inputs, throughputs & outputs being the conduit back to finance in the US for effect capacity forecasting - Input and strategy for comp based decisioning and benchmarking - Support leadership in overall regional operations & finance strategy across all functions, sales, pre, ecosystem etc - Evaluate new tools in market and be responsible for improving the efficiency and effectiveness of the sales team - Build and maintain dashboards, leaderboards, and pipeline reporting to give leadership real-time visibility. - Monitor deal progression and hold reps accountable for CRM hygiene and accuracy. - Support deal reviews at the pricing and negotiation stages, coordinating with outside counsel as needed. - Own the closed-won process from signature through handoff to post-sale. - Administer commission plans across the sales org, ensuring accurate and timely calculations and serving as the source of truth for comp-related questions. WHAT YOU BRING: - A builder's mentality; you identify gaps, propose solutions, and execute without being asked twice. - The ability to zoom out and think strategically while staying close enough to the work to get your hands on the keyboard. - An AI-forward mindset: you actively use AI in your work and are excited to pioneer its use in go-to-market operations. - Strong communication and collaboration skills; you earn trust across Sales, Marketing, and Finance. - A player-coach orientation; you're not above the details and you're excited to own the work yourself REQUIREMENTS: - 3–7 years in Sales Operations or Revenue Operations at a high-growth usage based sales organization - You've built core GTM infrastructure before: lead routing, CRM architecture, pipeline reporting, commission administration, deal desk. - Deep proficiency in workflows, lifecycle stages, custom properties, data hygiene. - You've owned commissions end-to-end: building the model, calculating payouts, fielding rep disputes, and keeping it reconciled with Finance. - You've run a deals desk, you know what makes a contract clean and you catch errors before they become problems. - Strong in Excel or Google Sheets; you can build a pipeline coverage model and know which metrics actually matter. - You've earned trust with a sales team by making their lives easier while holding them accountable to process.

Location: New York; San Francisco; London 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: As a Manager, Enterprise Sales, you will lead and scale our enterprise sales team, driving strategic revenue growth with a consultative, customer-first approach. You will oversee complex deal cycles, coach Enterprise Account Executives, and build the motion that wins high-impact, multi-stakeholder deals in a rapidly evolving AI landscape. WHAT YOU’LL DO: - Lead, mentor, and develop a team of Enterprise Account Executives, fostering a culture of performance, strategic thinking, and collaboration - Own and guide the full enterprise sales cycle, from targeted outbound and discovery to multi-threaded navigation, negotiation, and close - Build and refine enterprise sales playbooks, qualification frameworks, and forecasting models that increase accuracy and velocity - Collaborate cross-functionally with Product, Marketing, and Engineering to align on go-to-market strategy, unblock enterprise requirements, and deliver seamless customer experience - Drive pipeline generation strategy and help shape top-of-funnel programs - Establish enterprise sales processes, performance metrics, and best practices that ensure consistent quota attainment across the team WHO YOU ARE: - A proven enterprise sales leader with experience closing large, complex deals and managing high-performing teams - Skilled in multi-threading, stakeholder alignment, and navigating procurement, legal, security review, and executive-level conversations - A strong coach who helps Account Executives sharpen discovery, messaging, deal strategy, and negotiation - Highly strategic and structured, able to build repeatable systems and scalable enterprise sales motions - Comfortable owning forecasts, running deal reviews, and driving predictable revenue outcomes

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. THE ROLE: We are looking for 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 well suited to 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 improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. PREFERRED QUALIFICATIONS: 1. Currently pursuing a PhD in computer science, machine learning, or a related field. 2. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. 3. Experience developing and evaluating large-scale models or machine learning systems. 4. Familiarity with distributed training, large-scale inference, or multi-GPU environments. 5. Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR. 6. Strong programming and engineering skills, with the ability to translate research ideas into working implementations. 7. A collaborative, mission-driven mindset and the ability to work effectively across research and engineering teams.

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Location: New York; San Francisco 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 building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. WHAT YOU'LL DO: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to 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 improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. PREFERRED QUALIFICATIONS: - A PhD in computer science, machine learning, or a related field. Candidates with a master’s degree and significant research or industry experience will also be considered. - A demonstrated record of research accomplishments in reinforcement learning, machine learning, foundation models, or related fields. - Experience with large-scale training and inference infrastructure, including distributed systems and multi-node GPU clusters. - Experience developing, training, optimizing, or deploying state-of-the-art large-scale models. - First-author publications at leading venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, UAI, JMLR, or TMLR. - A mission-driven mindset and a strong desire to translate research advances into meaningful product impact. - A collaborative spirit and the ability to work effectively across research and engineering teams.

Location: New York; San Francisco 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: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. WHAT YOU'LL DO: - Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spiky serverless traffic, and whatever else the research agenda calls for. - Train custom speculators against real production traffic and feed what you learn back into target models -- acceptance length is the metric that decides the win. - Work directly with customers alongside our Forward Deployed Engineers to deploy and tune models, and bring what you learn back into the research. - Carry and expand collaborations with outside research labs, for example: - our work with ZLab on DFlash https://modal.com/blog/spec-is-all-u-need, a speculator design built on KV injection and blockwise parallel drafting - our work with SGLang on specdec https://modal.com/blog/host-overhead-inference-efficiency and multimodal inference https://modal.com/blog/boosting-multimodal-inference-performance-by-greater-than-10-with-a-single-python-dictionary performance - our work on Flash Attention 4 kernels https://modal.com/blog/flash-attention-4-faster - Work with engineering to turn frontier serving techniques into products: primitives for disaggregation, fast weight refresh for models that keep training after deployment, observability for quality and latency in production, or even a next-generation inference engine. - Help shape the research agenda. None of the above is prescriptive; your work will help guide our future. REQUIREMENTS: - A research-leaning or systems background in LLM inference, with work you can point to. - Fluency in the LLM serving stack, from kernels and quantization up to schedulers and autoscaling. - A record of shipping research or systems that other people build on, whether in a lab or in industry. - The drive to independently take a research bet from idea to result, working in the open with the rest of the team. - Ability to work in-person, in our NYC or San Francisco office.

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 People Operations Generalist to join our growing People team. You'll touch the employee lifecycle end-to-end — from offer acceptance through offboarding — while helping to build the processes and documentation that let our People function scale with the business. This is a great fit for a highly organized, systems-oriented people person who thrives in a fast-paced environment and wants to build operational foundations, not just maintain them. WHAT YOU’LL DO: - Own and continuously improve the new hire onboarding experience, ensuring employees are set up for success and internal tasks are tracked and completed on time. - Serve as a first point of contact for employee questions across the full HR spectrum, triaging and routing more complex issues to the right People team member or external partner. - Maintain and improve self-service resources (FAQs, Notion pages, etc.) so employees can find what they need quickly — and always feel supported even when no one's in the room. - Support rollouts of new People programs and policies, including communication planning, manager enablement, and documentation. - Help bring employee experience programs and events to life, from team offsites to milestone recognition, that reinforce culture and make people feel valued. - Process employee changes (promotions, equity refreshes) accurately and on time, including preparing updated employment letters and maintaining compliant employee files. REQUIREMENTS: - 2+ years of People Operations experience, preferably at a high-growth startup. - Demonstrated ability to build and document HR processes from the ground up, not just execute existing ones. - Strong written communication: you write clearly, keep things simple, and know your audience. - Experience managing employee data with accuracy and discretion. - Comfortable handling competing priorities without losing track of the details.

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 an Engineering Manager to lead a group of highly experienced engineers. This is a hands-on leadership role where you’ll spend roughly half your time on technical contribution and half on people management, depending on the need. You’ll 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. WHO YOU ARE: We think you are an experienced engineering leader who thrives close to the work and enjoys building alongside their team when needed. You earn trust through technical depth, communicate with clarity, and help great engineers move fast and make sound decisions. You thrive in a fast paced environment, you are pragmatic, calm under pressure, and focused on impact. REQUIREMENTS: - At least 10 years of industry experience, including 3 years experience in a leadership role - Experience building high-performance distributed systems at a large scale - Strong background in cloud infrastructure - Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) - Proficient in systems-level languages such as Rust, C, C++, or Java

175 000 – 250 000 $

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: We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary https://modal.com/gpu-glossary and LLM Engine Advisor https://modal.com/llm-almanac/advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. IN THIS ROLE YOU WILL: - Own and evolve Modal's marketing site, docs site, and technical web experiences as high-quality engineering systems, not static content. - Build bespoke interactive projects with engineers, turning deep technical work into useful web experiences for developers and agents. - Own Instrument all public-facing content, all the way from human-facing marketing pages to agent-targeted, self-improving documentation. - Improve internal publishing flows so more teams can ship quality content quickly while keeping the site maintainable. REQUIREMENTS: - Evidence of building and shipping modern web applications end-to-end. We care more about what you've built than years of experience. - Experience with agentic development flows where agents consume marketing content and docs to help developers build on Modal. - You can build polished, responsive web experiences without needing every detail specified. - Business-owner mindset with strong data intuition: you think about conversion, activation, developer trust, speed of launch, and quality of measurement and tradeoff inherent to each. - Excited about developer-facing AI infrastructure and building web experiences that feel credible to engineers. - Ability to work in-person in our NYC office. NICE TO HAVE: - Deep knowledge of SEO, AEO, structured content, or agentic discoverability. - Experience with marketing sites, docs sites, or product-led-growth surfaces at a dev tools / infra / AI company. - Familiarity with our stack: Svelte/SvelteKit, TypeScript, Tailwind, Vite, MDX/SVX content systems, headless CMS (Sanity), Playwright/Vitest. - Familiarity with our integrations: Segment, Snowflake, PostHog, Sentry, Algolia/DocSearch, Fillout, Pylon, Ashby. - Experience designing growth experiments, A/B tests, or funnel instrumentation. - A portfolio of polished sites, docs systems, interactive demos, or growth experiments.

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: We’re looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. WHAT YOU'LL DO: Platform & Runtime Security - Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) - Strengthen boundaries between customers, workloads, and internal systems - Identify and mitigate risks in distributed, dynamic compute environments Container & Orchestration Security - Secure and harden containerized workloads and orchestration systems (e.g., Kubernetes or similar) - Improve workload isolation, scheduling boundaries, and runtime protections - Evaluate tradeoffs in multi-tenant execution models Identity & Access Management - Design and improve authentication and authorization systems across services - Implement strong service-to-service identity and least-privilege access patterns - Improve access controls across infrastructure and internal systems Secrets & Key Management - Build and maintain systems for securely managing secrets, tokens, and credentials - Improve rotation, auditing, and access controls - Reduce secret sprawl and integrate secure patterns into developer workflows Cloud & Infrastructure Security - Secure cloud environments across providers (AWS, GCP, etc.) with a focus on consistency and portability - Improve network boundaries, service segmentation, and access controls - Embed security into infrastructure-as-code and deployment systems Engineering Partnership - Work closely with product and infrastructure teams to design secure systems from the ground up - Review architecture and code for security risks and provide actionable guidance - Identify patterns in risks and drive cross-cutting improvements REQUIREMENTS: Core Experience - Experience securing cloud-native infrastructure and distributed systems in production - Background in infrastructure, backend, or security engineering - Experience working in multi-tenant or high-scale environments Technical Depth - Strong understanding of containerization and orchestration systems (e.g., Kubernetes or similar) - Experience designing or securing isolation mechanisms in multi-tenant systems - Solid understanding of authentication, authorization, and service identity models - Experience with secrets management and secure handling of credentials - Strong foundation in networking concepts (segmentation, service communication, access boundaries) Mindset - Builder mentality, you design and implement, not just review - Pragmatic approach to security in fast-moving environments - Comfortable working deeply with engineers and influencing system design PREFERRED QUALIFICATIONS: - Experience with sandboxing or runtime isolation technologies (e.g., gVisor, Firecracker, seccomp, or similar) - Familiarity with kernel-level or low-level isolation primitives - Experience securing Kubernetes or similar orchestration systems in production - Background in developer infrastructure, compute platforms, or multi-tenant systems

Location: New York; San Francisco 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 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! REQUIREMENTS: - 5+ years of experience writing high-quality, high-performance code. - Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). - Familiarity with Nvidia GPU architecture and CUDA. - Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). - Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

200 000 – 350 000 $

Location: New York; San Francisco 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 Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: - Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on Modal - Contribute to open-source projects — members of the team are active contributors to SGLang — and publish technical content that demonstrates Modal's capabilities across the AI stack - Collaborate with Modal's product and sales teams, contributing to the platform as both an engineer and a product stakeholder - Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work - Conduct technical demos, experiments, and proof-of-concepts that make Modal's performance advantages tangible REQUIREMENTS: - 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure - Familiarity with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains. You don't need all of these, but you should be able to go deep on at least one. - Strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership - Genuine interest in working directly with customers — you find it energizing to understand someone else's problem and help them solve it - Bonus: side projects, open-source contributions, or published work you're proud of in ML or systems performance - Willing to work in-person in New York City, San Francisco, or Stockholm

Location: San Francisco; Stockholm; New York; London 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 is hiring a high-impact Solutions Architect to drive technical strategy across our most strategic enterprise accounts. You will operate as the executive technical counterpart to Enterprise Account Executives, leading complex evaluations, shaping infrastructure modernization roadmaps, and driving multi-product adoption across AI/ML workloads. This role is not demo support. It is a strategic, consultative position requiring strong architectural depth, executive presence, and the ability to influence 7–8 figure infrastructure decisions. You will work directly with CTOs, VPs of Engineering, and ML platform leaders to help them rethink how AI infrastructure should be built and operated. If you thrive in high-velocity technical sales environments and want to shape the infrastructure layer powering modern AI companies, this role is for you. WHAT YOU’LL DO: - Own the technical strategy for large, complex enterprise accounts - Partner with Enterprise Account Executives to drive 6–7+ figure opportunities from qualification through close - Lead deep technical discovery across platform, ML, DevOps, and infrastructure stakeholders - Architect end-to-end migration strategies from AWS, GCP, or Azure to Modal’s serverless infrastructure - Drive executive-level technical conversations that connect infrastructure architecture to business impact (velocity, cost efficiency, reliability) - Design and oversee proof-of-concepts that demonstrate production-grade scalability and performance - Navigate security reviews, compliance discussions, and procurement processes with confidence - Build durable relationships with technical champions and executive sponsors - Orchestrate cross-functional virtual account teams (Sales, Product, Engineering, Support) to ensure successful adoption - Influence Modal’s product roadmap by surfacing structured enterprise feedback - Mentor other Solutions Architects and contribute to technical best practices across the team REQUIREMENTS: - 5+ years in Solutions Engineering, Sales Engineering, or enterprise-facing technical roles in infrastructure, cloud, or developer platforms - Demonstrated success driving complex enterprise sales cycles ($250K+ ACV; experience with $1M+ ARR accounts strongly preferred) - Experience working with large, sophisticated Bay Area technology companies or global enterprises - Deep expertise in cloud infrastructure (AWS, GCP, Azure) including compute, networking, storage, and managed services - Strong architectural understanding of containers and orchestration (Docker, Kubernetes) - Experience designing distributed systems and production data platforms - Strong working knowledge of ML/AI infrastructure (training pipelines, inference systems, GPU workloads, MLOps) - Experience leading cloud migration or infrastructure modernization initiatives - Familiarity with Infrastructure as Code (Terraform, Pulumi, CloudFormation) and CI/CD systems - Production programming experience in Python strongly preferred - Executive-level communication skills with the ability to influence technical and business stakeholders - Proven ability to lead cross-functional virtual teams in high-stakes account environments - Strong business acumen and understanding of enterprise procurement and buying processes - Willingness to travel up to 30%

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: We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution 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, large-scale data handling, and performance optimization. WHO YOU ARE: You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answer itself. RESPONSIBILITIES: Team - Recruit, hire, and grow a high-performing team of cloud platform 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, and continuous improvement. Technical Direction - Drive day-to-day technical decisions through design reviews, code reviews, and architectural discussions. - Translate the infrastructure roadmap into clear team priorities and milestones, and hold execution against them. - Establish standards for reliability, performance, and operational excellence; ensure the team owns projects end-to-end, from spec through production. - Push for good judgment on tooling and architecture, with a bias against unnecessary complexity. Cross-Functional & Incident Leadership - Partner with product and engineering to align infrastructure work with business priorities; represent your team's progress, capacity, and tradeoffs clearly to leadership. - Serve as the escalation point for major incidents; drive resolution with urgency and ensure the team learns systematically, feeding those learnings back into infrastructure improvements. REQUIREMENTS: - 10+ years of industry experience, including 3+ years in a leadership role - Track record building high-performance distributed systems at scale - Strong background in cloud infrastructure - Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.) - Proficiency in a systems-level language (Rust, C, C++, or Java)

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: We’re looking for business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will: - Drive in-depth quantitative analyses to inform our pricing and packaging strategy. - Help spin up our deal desk and streamline enterprise deals. - Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities. - Implement new tools and processes to enable the GTM org to grow rapidly. - Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan. REQUIREMENTS: We are looking for someone who: - Has 5+ years experience working in some kind of business function (e.g. banking, consulting, startup). - Has some exposure to tech and coding (in order to understand our product & customer, work with analytical tools, and build out custom tooling). - Is analytical, organized and detail-oriented, holds their output to a high bar of excellence. - Is eager to learn about a variety of different business functions and juggle many projects at once. - Is excited about working in-person in NYC.

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: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: - Identifying architectural changes to improve reliability and performance. - Fostering a culture of reliability across Modal’s engineering organization. - Defining and implementing operational processes such as deployments, upgrades, etc. - Operating systems like Kubernetes, Postgres, Redis, etc. - Participating in on-call rotations, and responding to production incidents. REQUIREMENTS: - 5+ years of experience writing high-quality production code. - 2+ years of on-call experience for critical production services. - Strong cloud skills, and deep familiarity with at least one hyperscaler cloud (AWS preferred). - Familiarity with auto scaling, fleet management, and capacity planning at scale. - Experience operating databases, monitoring, CI/CD, and other infrastructure, at scale - Experience owning and scaling Kubernetes clusters to thousands of nodes a plus. - Experience with systems safety research (e.g. STAMP) and control theory a plus. - Ability to work in-person in our NYC or Stockholm offices.