Infrastructure Jobs

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. About the role As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines. Join us in our mission to develop advanced AI systems pushing the frontiers of science and benefiting humanity. Responsibilities: Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI. Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows Collaborate to translate experimental requirements into production-ready infrastructure Develop large scale data pipelines to handle advanced language model training requirements Optimize large scale training and inference pipelines for stable and efficient reinforcement learning You may be a good fit if you: Have 6+

About Navier AI Navier AI is building the first autonomous engineering agents. AI systems that can design, simulate, and optimize complex products to achieve breakthrough levels of performance. Our mission is to enable engineers to move beyond today’s slow, manual design cycles by providing agents that reason about physics, explore design trade-offs, and generate high-performance solutions across aerospace, automotive, and advanced manufacturing. We’re backed by top-tier investors and work directly with industry leaders to deploy AI-native tools that go far beyond today’s design automation. Role Overview We’re hiring a Full Stack Engineer to build the interactive interfaces and backend services that power our autonomous engineering agents. You’ll be responsible for creating seamless user experiences that let engineers visualize complex geometry, interact with AI agents, and manage design workflows—all while collaborating closely with ML, backend, and simulation teams. Responsibilities Build interactive web applications using TypeScript, React, and Three.js to visualize CAD models, simulation results, and agent outputs Develop backend services in Python to power workflows, handle model inference requests, and manage user data Design intuitive UIs and workflows that make AI-powered engineering agents accessible and useful to domain experts Implement real-time rendering and 3D visualization pipelines for CAD, meshes, and simulation outputs Collaborate with ML and backend engineers to connect front-end tools with AI models and simulation infrastructure Ensure application performance and scalability through robust state management, API design, and efficient data handling Participate in architecture discussions and help define best practices for frontend + backend integration Own features end-to-end, from design to deployment, in a fast-paced startup environment Qualifications Required Strong proficiency in TypeScript and React Experience building 3D interactive ex

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world. About the program Binance Accelerator Program is a concise fixed-term program designed for Early Career Talent to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the worlds’ leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about BAP Program HERE Who may apply Current university students and recent graduates About the team The Binance Wallet team is building a decentralized version of Binance, featuring on-chain infrastructure, self-custody wallets, a DEX, decentralized Earn, and more. We empower users with full control over their assets for seamless token trading across any blockchain. This Web3 initiative expands our strategic landscape and complements our CEX business, offering significant growth potential. Join us and be part of this exciting journey. Responsibilities Collect and analyze community feedback to provide actionable insights to internal teams to help formulate product development and marketing strategies Assist the team lead to implement structured workflow, guidelines and imp

About us Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor and Clay Bavor . Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. Security Engineer Security Engineering builds the foundations that let Sierra deliver powerful AI agents while protecting customer data and trust. We partner across product and platform to make security, privacy, and safety core product capabilities and secure defaults. What you’ll do Our work spans several security domains. You’ll go deep where your strengths and interests are strongest, with opportunities to explore new areas alongside the team. Build the Foundations of Trust. Design and ship systems and controls that make Sierra secure by default — spanning product security, infrastructure security, enterprise security, identity, and detection and response. You’ll work across all layers of our platform to identify risk, strengthen architectures, and buil

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: Perform engineering efforts focused on improving model serving, inference performance, and system efficiency Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability Partner closely with research and product teams to ensure our models perform effectively at scale Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: Have deep expertise in model performance optimization, particularly at the inference layer Have a strong background in kernel-level systems, data movement, and low-level performance tuning Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads Can navigate ambiguity, set technical direction, and drive complex initiatives to completion This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. About OpenAI OpenAI i

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

About the team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you'll: Create ambitious RL environments to push our models to their limits, and measure frontier

Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. What You'll Do Be a part of a team owning the entire product lifecycle - from early ideation and R&D through to deployment and long-term maintenance. Architect resilient embedded systems; conduct validation to verify correctness against technical constraints and functional requirements. Build high-performance features across Verkada’s embedded Linux device ecosystem (Cameras, Access Control, Alarms, and Environmental Sensors) prioritizing seamless user experiences. Extend core backend services implemented in Go and Python. Improve and maintain internal developer tools and infrastructure to streamline product delivery. Investigate, diagnose, and resolve critical technical issues directly impacting field devices and end users. Travel to partner foundries and manufacturing facilities to support new hardware bring-up and validation. What You Bring

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on

🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts , accounts for 16-17 year olds , a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save , invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo ❤️ 📍Barcelona, Spain | 💰 Base salary for this role is depending on experience + Incentive Awards tied to your performance + benefits Hybrid model: 3 days a week in the office About our Engineering Teams: We have over 650 engineers across Monzo who design and build our in-house banking platform. We have big ambitions for the future, and technology plays a big role in creating a bank our customers want, so engineers at Monzo collaborate across disciplines to solve interesting challenges throughout the company. These range from the products our customers use everyday to underlying infrastructure, security, payments and finance, customer operations, financial crime, and data, to name just a few areas. As a bank, there is scope for impact across a huge number of opportunities. We contribute to open source software as much as possible. Our blog is a good place to learn even more about what we do! Your day-to-day This role is all about collaborating with your team to make a difference to your customers. As a backend engineer you’ll work in a squad alongside other disciplines like product managers, marketers, us

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Summary: We are seeking a highly motivated and skilled Akamai CDN & WAF Engineer with 2-5 years of hands-on experience in configuring, deploying, and managing Akamai's Content Delivery Network (CDN) and Web Application Firewall (WAF) solutions. The ideal candidate will possess a strong understanding of web performance optimization, security best practices, and have a proven track record of implementing and troubleshooting Akamai services in a production environment. This role requires a proactive individual with excellent problem-solving skills and the ability to collaborate effectively with cross-functional teams. Responsibilities: Configuration and Deployment: Configure and deploy Akamai CDN services (e.g., Domain onboarding, delivery rules, caching policies, origin configurations) and WAF rulesets (e.g., security policies, custom rules, DOS and client reputation) based on application requirements and security guidelines. Production Support: Provide day-to-day operational support for Akamai CDN and WAF infrastructure, including monitoring performance, identifying and resolving issues, and implementing necessary changes. Performance Optimization: Analyze website performance metrics and implement Akamai CDN features and configurations to optimize website speed, reduce latency, and improve user experience. Security Implementation: Implement and manage Akamai WAF policies to protect web applications from various security threats, including OWASP Top 10 vulnerabilities, bot attacks, and DDoS attacks. Rule Management: Create, review, and maintain custom WAF rules and exceptions based on application-specific ne

Perplexity is looking for a highly skilled Senior or Expert Systems Engineer to join our Search Core team. This role is critical to building next-generation search products and technologies. You will help drive key decisions around the architecture, design, and implementation of foundational components in our technical stack. Responsibilities Design and build core search engine components, including indexing pipelines, retrieval algorithms, and ranking systems that operate at the scale of billions of pages Develop streaming and batch data processing systems for search index construction in a high-load environment Push the limits of hardware performance through low-level optimizations and systems-level tuning Tackle challenges in multithreading, concurrency, and system-level optimization Qualifications 3+ years of hands-on experience in systems programming (Rust, C++, C, or similar) Ownership of full project lifecycle — you don't just write a fast inner loop, you care about how the system is built, deployed, operated, and scaled in production Knowledge of Python or other scripting languages Passion for writing clean, efficient, and scalable systems-level code Strong knowledge of algorithms and data structures, and the ability to apply them effectively Deep understanding of multithreading, including various approaches, challenges, and trade-offs Experience building high-load, distributed, and hardware-adjacent services Solid understanding of Linux internals (syscalls, networking stack, memory model, kernel tuning) Familiarity with low-level optimization techniques (memory management, cache efficiency, SIMD, profiling) Preferred Qualifications Experience developing core components of search engines, databases, or information retrieval systems Understanding of search fundamentals: indexing, query parsing, ranking, and relevance Experience with trading systems or other latency-sensitive real-time systems Familiarity with cloud services, Kubernetes, and AWS infrastructure

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us—that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale—from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Nuro's autonomous vehicle platform has to work - not just in the easy cases, but in the hard ones. The ones we design for, simulate at scale, and deliberately break to understand. We're looking for a Senior/Staff Systems Engineering TPM who owns the technical substance of how we validate autonomy: what we test, why we test it, and whether our coverage actually means something. This is not a planning or scheduling role. You'll work embedded with Autonomy, Simulation, and Systems Engineering teams to drive the technical rigor behind our validation program — defining scene sets, structuring fault injection campaigns, and ensuring our simulation coverage is meaningful, traceable, and systematically growing. The program infrastructure is owned elsewhere; your job is to make sure what's inside it is technically sound. About the Work Scenario & Coverage Strategy Understanding the taxonomy of challenging scene sets used for auto