It System 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 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

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This role owns a product area end to end. Where the product marketer is the market lens, you are the person accountable for what we build, how it works, and whether it ships and succeeds. You lead a cross-functional team of engineers, designers, and applied AI specialists to turn strategy into a product members rely on. You own the roadmap for your area, the decisions inside it, and the outcomes it produces. You work at the center of the product organization, translating a clear point of view into shipped work that moves MINERVA and the COGENT architecture forward through each GR/GA milestone. Why this role exists In an AI market where capabilities can be copied in weeks, the advantage goes to teams that decide well and ship fast. Someone has to hold the point of view, make the calls, and keep a team building the right thing. Collective intelligence is hard product work: reasoning over messy knowledge, earning member trust, and fitting into how communities already operate. It needs an owner who can hold both the ambition and the details. The Senior Product Manager is that owner. You set direction for your area, make the hard prioritization calls, and are accountable fo

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 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 . The Team Pinterest's Shopping & Delivery Infrastructure team builds and operates the catalog, indexing, retrieval, and serving systems that power Shopping and ads across every Pinterest surface, from search and homefeed to P2P and international markets. Our mission is to make Pinterest's shopping and delivery stack unified, scalable, and low-latency so we can drive sustainable revenue growth, exceptional Pinner experiences, and measurable advertiser outcomes. We're in the middle of a multi-year transformation of the stack, and we work closely with catalog, indexing, retrieval, serving, ads quality, and product teams to make Pinterest's shopping infrastructure faster, more reliable, and ready to scale. What You'll Do Independently drive a well-defined portfolio of Shopping catalog and indexing programs, keeping engineering owners, timelines,

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 . The Team Pinterest's Ads Delivery Infrastructure team builds and operates the real-time serving, indexing, retrieval, and budgeting systems that power Shopping and Ads at Pinterest. We're in the middle of a significant modernization effort: unifying our catalog and index platforms to scale to billions of items, moving core services onto our next-generation compute platform, and re-architecting our budgeting systems for real-time accuracy. We work closely with engineering, product, and monetization teams to keep Pinterest's advertising systems fast, reliable, and ready to scale. What You'll Do: Lead or support programs that scale Pinterest's Shopping and Ads catalog, indexing, and retrieval systems to handle billions of items, partnering with engineering leads across catalog, search infrastructure, and retrieval. Drive cross-team execution on inf

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the team The Applied AI Engineering team ensures our customers get the optimal experience from DevRev. As customers go through their DevRev journey, they may identify needs for integration with existing enterprise systems and services, workflow and process automation, or customization of the DevRev platform to achieve their business objectives. Our team works with customers to understand requirements and design, develop, and implement solutions to meet customer goals. Your mission is to systematically help customers find value with DevRev by developing a thorough understanding of their needs, owning coordination between internal and external stakeholders, and engineering the solution to get the job done. You are a product expert and will use your application development and AI/ML skills to ensure our customers get the most out of the DevRev platform. About the role As a Forward Deployed Architect, you will serve as a hands-on senior technical architect on the Applied AI Engineering team, owning the end-to-end design and delivery of AI-driven business transformation projects. You will work closely with pre-sales teams to scope technical integration and implementation strategies, translating business requirement

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. Realizing that vision requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build Replit's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and decisions that protect Replit's users, platform, and economics. You'll work closely with Engineering, Support, Legal, Security, Infrastructure, Money, and Growth to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse rate to understand selection effects, missing labels, policy changes, attacker adaptation, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and outcomes are high stakes. Ground truth is delayed, biased, and often incomple

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 you’ll do: Develop measurement frameworks and metrics to drive data-driven decision making, optimizing for the full user journey. Product recommendations. Clearly communicate recommendations to product and engineering leadership on how we can evolve our Notifications strategy to address shortcomings observed through deep analysis. Opportunity sizing and analysis. Write clear, actionable analyses that help teams identify areas of improvement to our growth strategies. Thought partner to product, engineering, and ML leadership on the Notifications team to prioritize/scope projects and inform the development of the notifications user experience and corresponding ML systems. Improve machine learning models which power notifications delivery and content, via direct contributions, new features/signals, and/or compelling analy

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 . This role focuses on advancing the science and systems behind ML measurement, feature understanding, and causal inference at scale. The work spans areas such as production feature importance platforms, observational causal estimation in Pytorch, large-scale proxy metric development, and data-driven approaches to ML infrastructure efficiency. We're looking for an enthusiastic individual contributor to perform high-impact technical work across this space. This person will drive foundational innovations, own the end-to-end design of production ML systems, establish rigorous methodological standards, and partner cross-functionally to turn successful research into durable platform capabilities that raise the ceiling for the entire ML organization. What you’ll do: We are looking for an experienced and highly capable Data & Applied Scientist

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 . Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business. We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical fram

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We're looking for a Technical Program Manager who can operate at the intersection of engineering, product, and business — someone deeply technical, trusted instinctively by engineers, and sharp enough to drive clarity and momentum across complex, cross-functional programs. This is a high-agency role with real executive visibility and direct impact on how Ramp's engineering organization scales. We're looking for someone who is energized by complexity, deeply curious about what AI can unlock for engineering teams, and eager to apply it hands-on in their work. You should be someone who experiments with AI tools regularly, thinks about how they change the way software gets built, and brings that perspective into how you run programs. What You’ll Do Lead large-scale technical programs across engineering and adjacent teams—from CI/CD and infrastructure scaling to incident response, and driving other strategic projects across the engineering organization Own Ramp's engineering incident response program, improving processes, running retrospec

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. We are looking for a Security Operations Lead (SOC Lead) to build, mature, and operate our 24/7 detection and response capabilities across a modern cloud-native and AI-driven environment. This role leads the global SOC function—monitoring, SIEM ownership, detection engineering, alert triage, and operational readiness—while also evaluating and integrating emerging AI-based SOC products and autonomous response platforms . You will oversee monitoring across multi-cloud environments (GCP primary, AWS/Azure secondary), Kubernetes, SaaS services, endpoints, developer tools, and AI workloads . You’ll collaborate closely with Cloud Security, Compliance/GRC, SRE, Platform Engineering, IT/Endpoint teams, and AI Infrastructure to ensure our detection strategy scales and stays ahead of evolving threats. This is a hands-on leadership role perfect for someone who wants to shape the SOC of the future while solving complex challenges in a high-scale AI setting. What You’ll Do SOC Leadership & 24/7 Monitoring Lead, mentor, and scale a global SOC team responsible for 24/7 monitoring, alert intake, triage, correlation, and escalation. Build operational rigor: processes, runbooks, SLAs, metrics, and quality standards for high-scale environments. Cover monitoring across: Cloud infrastructure (GCP, AWS, Azure) Kubernetes/GKE/EKS/AKS clusters SaaS platforms (Google Workspace, GitHub, Slack, Okta, etc.) Endpoints (macOS, Linux, Windows) including EDR/XDR telemetry Developer platforms + CI/CD pipelines AI/ML systems and model-serving workflows AI-Based SOC Integration & Innovation Evaluate, adopt, and integrate AI-native SOC technologies for triaging, detection, and correlation Identify opportunities to automate triage, investigations,