Experienced Or Senior Digital Design Engineer in 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 Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're hiring a Compute Strategy and Operations lead to own how Modal plans for and acquires GPU and CPU capacity. You'll size our infrastructure needs ahead of demand, source supply across hyperscalers, neoclouds, and datacenter operators, and negotiate and close the contracts to secure it. The compute you secure directly determines what Modal can sell and build. In this role, you will: Own end-to-end procurement of GPU and CPU capacity across hyperscalers, neoclouds, and datacenter operators Build and maintain a strong pipeline of supplier relationships Evaluate supply options on price, availability, hardware specs, networking capabilities, and SLA terms Negotiate and close contracts: reserved capacity agreements, spot arrangements, MSAs, DPAs, and order forms Work closely with our engineering teams to translate technical requirements into procurement specs Track

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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 answ

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. 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 infrastructure 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 deploy massive-scale production workloads on Modal Lead technical discovery and architect

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re hiring an Enterprise Account Executive to accelerate Modal’s growth with the world’s most innovative AI companies. This is a high-impact role where you’ll own the full sales cycle—from building pipeline to closing large, strategic enterprise deals. You’ll partner directly with our founders, engineering, and product teams to help customers harness Modal’s infrastructure to train, deploy, and scale AI applications. You’ll be expected to operate as a builder: developing new relationships, shaping our GTM motion, and serving as the voice of the customer inside Modal. The ideal candidate is both technically curious and commercially driven—equally comfortable in a room with C-level executives and with machine learning engineers. In this role, you will: Drive new business by generating pipeline, negotiating, and closing complex enterprise deals Build deep, trusted r

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're hiring a VP of Finance to build the finance function from the ground up as our first full-time finance hire. This is a high-impact role for someone who thrives at the intersection of strategic thinking and hands-on execution. We are looking for someone who can architect the systems and processes that will scale with Modal, partner closely with the founders and executive team, and grow into the company's CFO. You'll report directly to the CEO and collaborate closely with our BizOps, GTM, and Product teams. In this role, you will: Build and maintain Modal's operating model, tying financial performance to company KPIs and resource allocation Lead all budgeting, forecasting, and long-range planning processes, and develop the reporting infrastructure that gives leadership and the board clear, timely visibility into the health of the business Partner with the found

AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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 en

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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 spik

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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 infrastruc

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), 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 robustnes

Company Description Novo is a venture-backed fintech that simplifies banking for small businesses. Since our Fall 2018 beta launch, we've expanded offerings from free checking accounts and debit cards to lending products, business tools (invoices, bookkeeping, and more), and integrations.Today , Novo is a powerfully simple banking platform that serves over 250,000 small businesses. In addition to providing smart tools built for entrepreneurs to better run and grow their businesses, Novo has processed billions in transactions in partnership with a number of established banking partners. Our vision is to be the go-to platform serving small businesses – from launch to everyday – so business owners can focus on growing, while Novo provides seamless money movement, money storage, and access to capital. We'd like to look back 5–10 years from now and know that we helped new generations of small businesses succeed because of the work we did at Novo. Novo raised $170 million in venture capital and is backed by leading investors, including Stripes, Valar Ventures, Crosslink Capital, and Notable Capital (formerly GGV). Learn more at https://www.novo.co . Role Description Novo is seeking a highly experienced and motivated product manager to own and scale our core banking experience — the accounts, money movement, cards, and program infrastructure that power banking for over 250,000 small businesses. This role is critical to ensuring the reliability, usability, and depth of the products at the heart of Novo, supporting our rapidly expanding customer base and business operations. The ideal candidate is a hands-on product leader who can set product direction for complex, regulated financial products, partner closely with Engineering, Design, Risk, and Compliance, and work hand-in-hand with banking partners to ship reliable, secure, high-quality experiences within a dynamic, regulated fintech environment. Responsibilities Product Strategy & Leadership Own the strategy, roadmap,

We are Datadog's in-house product experts. The Technical Solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. Premier Support Engineers (PSEs) are primarily focused on assisting prospects and customers with any technical questions about Datadog. PSEs engage with Datadog’s Premier Customers via standard technical support channels, but are also involved with cadence calls, demos/presentations, conferences, and various side projects. You will work directly with Datadog’s Premier Customer base, and will be immersed in a fast-paced environment where you will be challenged, but will also immediately witness your contributions to Datadog and to our customers. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Respond to client requests (phone / chat / tickets) on our fast paced team while continuing to educate our clients on the use of the platform Develop relationships with our Premier Customers, working hand-in-hand to truly know their distinct environment Reproduce issues and dive into the 600+ integrations that Datadog works with Build out documentation and knowledge based articles for a variety of technology Drive product conversations based on needs and problems learned during client interactions Participate in routine health check meetings with Premier Customers Work from a Datadog office 3 - 5 days per week Who You Are: Experienced in multi-channel technical support at a SaaS company (2+ years of related experience) A tinkerer with some programming experience and a basic knowledge of Linux Self-motivated, detail-attentive, and have a desire for continuous learning A critical thinker who defaults to a client-centric approach A decision

In this competitive market, the Group Product Manager for Cloud Security will play a mission-critical role in providing product and strategy leadership to grow Datadog’s market share through differentiation, innovation and compelling customer value. This leader will lead a talented and growing team of product managers and work with world class engineers to build and grow multiple Cloud Security products that play an essential role for our customers’ cloud security programs, and growing Datadog into a security industry leader. You Will: Run and grow multiple Cloud Security products to meet revenue and business targets with the goal of building a multi-hundred million dollar annual business. Lead and own product strategy and roadmap for accountable security products, fully aligned to revenue and business goals and with compelling differentiation and customer value. Ensure predictable roadmap execution across direct and partner teams to achieve product and business outcomes required to meet the revenue and business goals. Analyze and develop pricing and packaging strategies to maximize revenue through attaching deep understanding of market dynamics and other strategic leverage points. Drive GTM strategy with GTM partner teams to achieve revenue and business goals Fulfill the role as the product-leader representative across accountable product lines with analyst, press and customer communities Manage and grow individual contributor (IC) Product Managers, ensuring they are motivated, delivering high quality work and finding high fulfillment. Model and contribute to a culture of learning and collaboration across product management and the broader organization Raise the bar of PM leadership through leadership in strategy development, roadmap planning and execution, GTM and overall product-leader responsibilities. You Are: An experienced leader in Product Management with demonstrated business growth and customer adoption success in the CNAPP, data and AI