It Storage Engineer in United States

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 are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

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 are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

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 are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

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 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).

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 strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

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 strong engineers with experience building developer tools that users love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful interfaces that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python libraries with broad user-bases, ideally including some experience maintaining open-source software. Knowledge of advanced Python features, especially async programming. A strong product sense that manifests as a focus on developer ergonomics and productivity. A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our NYC or Stockholm office. Any of the following would be a plus:

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 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 and LLM Engine 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:

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 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: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

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

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . What We're Looking For: 2–4 years of program or project management experience (or equivalent), ideally touching infrastructure, platform, or cloud environments. Working knowledge of cloud platforms (AWS or similar) — compute, storage, and basic usage/cost concepts. Interest in, and some exposure to, capacity management and infrastructure efficiency (right-sizing, utilization, waste reduction); deep FinOps expertise is not required. Strong organizational and execution skills: able to track a program's moving pieces, follow up, and keep things on schedule. Clear written and verbal communication; comfortable presenting status and asks to engineering partners. Collaborative and coachable — works well with engineers and more senior TPMs, seeks input, and takes feedback well. Experience at a large-scale consumer tech or infrastructure organization is

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary The Senior Director, Semiconductor Sourcing and NPI Procurement leads the global strategy, sourcing, and supplier ecosystem for wafer foundry services, IP and EDA services, discrete actives semiconductors, and 3rd party NAND flash controller categories as well as the New Product Introduction Procurement function. This role is accountable for delivering cost competitiveness, supply assurance, and long-term resilience across a complex semiconductor value chain. Partnering closely with engineering, manufacturing, and business leaders, the role drives category strategies, supplier performance, and risk mitigation at category and product level while enabling Micron’s growth and innovation priorities. Success in this role requires deep semiconductor domain expertise, strong commercial acumen, and the ability to lead large, global teams to deliver enterprise-level outcomes. Main Responsibilities Define and execute global procurement strategies for wafer foundry services, IP and EDA ser

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 About the Role We're hiring the first Account Managers at Modal. You'll report to the Regional Director of Account Management and be a founding member of the team. This function does not exist yet. There is no playbook, no territory map, no established motion. You'll own a book of business from day one and build the motion at the same time — from fast-moving AI startups to large enterprise teams running critical infrastructure on Modal. This is a commercial role with a revenue target. You'll be measured on retention and expansion across your accounts. While you won't be delivering the technical recommendations and implementation, the work is technical by nature. Our customers are engineers running GPU workloads, inference, and batch jobs in production, and you need to hold your own in those conversations. The profile we're hiring is a technical account manager. You've worked at companies that are deepl

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As an Intern Product Yield Enhancement (PYE) Engineer at Micron Technology Inc., you will assist in taking next generation DRAM devices from design to mass production! PYE Engineers are crucial partners between Research and Development, Manufacturing, Product Engineering and Global Quality teams. Our goal is to offer hands-on and substantial engineering projects that allow interns to gain valuable experience with memory systems and the product life cycle while adding impact to Micron’s business. Our intern programs help prepare engineers for future roles and offer an extraordinary experience that supplements your academic experience! The PYE Engineering role is critical to Micron as it serves the company's charter to be the most cost-effective producer of DRAM memory while delivering the quality and reliability that customers expect from the Micron brand. This position is for a 3-month internship. Responsibilities: Your job duties will include detailed DRAM electrical and physical failure analysis. Identify defects introduced by the semiconductor fabrication process. You will data mine using statistical analysis, AI assisted engineering tools, and automation workflows. Find the root cause of failure mechanisms, communicating results with Management, Product, Process and Test Engineering teams. Complete 3-month internship. Minimum Qualifications: Must be pursuing a minimum of a bachelor’s degree in Electrical Engineering, Computer Engineering,

Senior Infrastructure Architect — Enterprise Observability and Automation Description - Job Summary Senior individual contributor responsible for the architecture, implementation, and operational ownership of enterprise observability, monitoring, and automation platforms across HP's global IT environment. This role modernizes infrastructure visibility capabilities while ensuring operational stability, security, and compliance. Serves as a technical and operational bridge between infrastructure engineering, cybersecurity, SOX/compliance stakeholders, automation teams, and external technology partners — leading complex initiatives such as platform migrations, enterprise integrations, and governance enablement. Responsibilities Enterprise Observability and Monitoring Application owner and senior technical authority for enterprise monitoring and logging platforms (Datadog, Splunk), including platform governance, roadmap alignment, and operational oversight. Lead enterprise-scale monitoring platform migrations, including architecture design, agent strategy, data ingestion models, vendor coordination, and deployment across 5,000+ servers. Define standards for alerting, dashboards, observability data quality, and integration with ITSM platforms (ServiceNow). Design and manage multi-org Datadog architecture, including org structure, RBAC, SSO/SAML, secrets management, and cybersecurity compliance. Oversee SNMP-based monitoring of storage and network devices, including device profiling, syslog/event integration, and NetFlow collection. SOX Compliance and IT Governance SOX control owner for enterprise monitoring applications — approve monthly reviews, participate in internal/external audits (EY), and maintain ITGC/SOX compliance. Provide audit evidence, walkthrough docu

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE You will be the strategic owner and revenue driver for Pure Storage's most valuable Enterprise accounts across the greater Chicago area. Your mission is to evangelize our radically simple, all-flash data platform, driving value that redefines the customer experience and maintains our industry-leading satisfaction. You will lead cross-functional pursuit teams, coordinating with sales specialists and strategic partners globally to execute and win new business. This role offers the autonomy to craft and execute a robust, territory-wide sales strategy with massive financial and technological impact. Location and Territory: Chicago WHAT YOU'LL DO Own a robust sales pipeline for your assigned territory, ensuring consistent activity and accurate forecasting that meets or exceeds quarterly and annual revenue quotas. Develop and execute comprehensive account strategies , mobilizing internal resources (Solutions Engineers, Marketing, Executives) to deliver Pure's total value proposition to key IT and business leaders within your Enterprise customers. Deepen relationships with C-level executives and key decision-makers to establish Pure as a long-term strategic partner, directly contributing to the industry's highest customer satisfaction ratings. Lead complex, multi-stakeholder sales cycles from initial contact to final contract, effectively orchestrating team-selling efforts with both internal peers and external str