We are looking for an enthusiastic software engineer to join our AI networking acceleration team, to work on a groundbreaking open-source library, using hardware offloads, GPU Kernels and RDMA network cards. Our product is a performance-oriented low-level infrastructure, crafted to change the way inference works. We thrive as a team in a deeply strong environment, and we're passionate about innovation. The rewards are sweet and include working with some of the brightest people in the industry, an aggressive compensation plan that rewards top performers, and the opportunity to collaborate on products that transform daily the way people work and play. What you'll be doing: Developing a highly optimized inference framework Running on the world’s largest supercomputers and data centers. The work environment is dynamic and challenging as our employees work on innovative, next-generation products at the forefront of technology in terms of performance, scalability, and features. What we need to see: B.Sc. or equivalent experience in Computer Science or Software Engineering 6+ years of experience in modern C++ / C / Rust development 3 years of experience in Linux environment and familiarity with development tools Deep knowledge of the TCP/IP network stack Understanding of computer architecture and operating systems concepts Ways to stand out from the crowd: Background in Linux internals and low-level software optimizations (benchmarking, bottleneck research, performance tuning) Experience in programming CUDA kernels is an advantage Familiarity with ML frameworks and LLMs Background in parallel programming / high-performance computing / RDMA t
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We are hiring senior engineers to work on the CUDA driver, a core component of our platform for accelerating general purpose computation on the GPU. Our team delivers features and improvements to better realize the potential of NVIDIA hardware for a growing range of computational workloads, ranging from deep learning, scientific computation, and self-driving cars to video games and virtual reality! CUDA defines a unified programming model across a range of system configurations and hardware capabilities. To accomplish this, the CUDA driver interacts with GPU hardware, kernel mode drivers, switches and the operating system. What you'll be doing: As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best Compute platform in the world. You will craft elegant solutions to exciting problems and craft the future direction of CUDA as you collaborate with your peers across NVIDIA. You will evangelize, architect, and implement new CUDA features You'll oversee and drive development efforts across multiple teams Collaborate with members of hardware architecture teams Help define forward-looking improvements to the CUDA APIs and programming model Design and maintain performance and precision modeling Write effective, maintainable, and well-tested code Develop code for multiple operating systems What we need to see: Bachelor of Science or Master of Science degree in Computer Science, Electrical Engineering, or related field (or equivalent experience) 15+ years of relevant systems software development experience Strong C programming skills </
Graphcore Senior Principal AI SoC Validation (Bring-up lead) Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. We are developing the next generation of AI compute, a large-scale system-on-chip (SoC) designed to power future high-performance AI systems. As the SoC Validation Lead, you will be responsible for enabling pre-production software to run reliably on new silicon quickly and efficiently, before showing that the silicon meets the highest standards of quality, reliability and functionality, ready for production deployment. You will lead a team delivering post-silicon validation across the full AI SoC, working across silicon, firmware, and platform levels. The role requires a deep technical understanding, strong hands-on debug experience, and the ability to collaborate effectively with hardware, software, and systems engineering teams. Key responsibilities Define and lead post-silicon validation strategy Develop and refine the overall post-silicon validation approach for our AI SoCs, ensuring reliable and timely delivery of validated silicon, architectural correctness, feature robustness, and at-scale system reliability. Drive cross-domain debug and issue resolution Lead investigation and resolution of complex issues spanning silicon, firmware, operating systems, and platform interactions. Ensure that fixes are effective and sustainable. Promote collaboration and shared understanding Work closely with
About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1–2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. 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. Key Responsibilities Support the development and maintenance of performance modeling tools and frameworks Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems Help analyze distributed system scaling behavior and identify performance bottlenecks Run simulations and analytical models to support architecture and infrastructure decisions Partner with senior engineers to evaluate design tradeoffs across hardware and system components Interpret modeling outputs and help translate findings into clear recommendations Vali
About the Team DoorDash Labs, established in 2018, serves as the innovation hub for DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. The team's mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We’re ruthlessly focused on business impact. We are a highly senior team composed of former pioneers from a variety of different robotics industries. As of 2025, DoorDash has completed 10B lifetime deliveries. We’re focused on how to do the next 10B even better. About the Role We’re looking for a Senior/Staff electrical and firmware engineer who designs the board and writes the firmware for connected consumer and enterprise devices, including tablets, POS systems, peripherals, and emerging robotics applications. In this role, you will take connected devices from ambiguous user or business needs through system architecture, rapid prototyping, board design, firmware implementation, bring-up, field deployment, and production transition. The ideal candidate has a passion for building and shipping reliable hardware at scale and thrives in an environment that demands technical depth and high-quality execution across multiple concurrent programs. This is a build-heavy role on a small, senior team. You’re excited about this opportunity because you will… Own connected devices end to end, including: Own connected devices from an ambiguous product need through field deployment. Work across the hardware and firmware boundary instead of handing work between specialists. Explore uncertain product ideas through rapid prototypes and experiments. Make consequential tradeoffs on a small, senior team with direct exposure to users and field behavior. Key Responsibilities Translate user and business needs into an integrated electrical and firmware architecture. Design compute-based, mixed-signal boards incorporating processors
NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated
WHO WE ARE: Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. WHO YOU ARE: We are looking for a Network Security Engineer with deep Zscaler expertise and a well rounded background in cloud and enterprise networking. This role centers on the deployment, administration, and optimization of Zscaler Internet Access (ZIA) and Zscaler Private Access (ZPA), while also supporting broader network security initiatives, including Cisco Meraki infrastructure and AWS cloud networking. The ideal candidate is a hands-on engineer with strong security instincts, a problem solving mindset, and experience managing both on-prem and cloud-based networking environments. WHAT YOU’LL DO: Lead the design, deployment, and optimization of Zscaler ZIA and ZPA across the enterprise. Manage Zscaler policies, including SSL inspection, URL filtering, access control, and zero trust configuration. Serve as the subject matter expert for Zscaler, owning integrations, troubleshooting, and escalations. Configure and support Cisco Meraki networking hardware, including firewalls, switches, and wireless infrastructure. Architect and manage AWS networking, including VPC design, Transit Gateway, NACLs, Security Groups, and routing. Develop and implement network segmentation and secure access strategies using both cloud and on-prem tools. Create and maintain detailed network documentation, runbooks, and security standards. Automate and streamline network ma
About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary The Workplace Coordinator is responsible for the day-to-day operation and maintenance of workplace infrastructure, ensuring that all building systems operate efficiently, safely, and reliably. This role oversees HVAC systems, including chillers and AHUs, Building Management Systems (BMS), electrical panels, and coordinates preventive and corrective maintenance activities to support uninterrupted business operations. Key Responsibilities Technical Operations · Monitor and maintain HVAC systems including Chillers, AHUs, FCUs, and ventilation systems. · Operate and monitor Building Management System (BMS) for alarms, trends, and equipment performance. · Inspect electrical LT panels, UPS systems, DG synchronization (if applicable), and power distribution systems. · Monitor critical utilities including temperature, humidity, pressure, and energy consumption. · Ensure uninterrupted operation of critical infrastructure and respond promptly to system failures. Preventive & Corrective Maintenance · Plan and execute preventive maintenance schedules for HVAC and electrical systems. · Coordinate breakdown maintenance with
The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record. We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all. The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you. At Datadog, we place value in our office culture: the relationships and collaboration it builds, and the creativity it bring
We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Enterprise Solutions – Connected Stores team is building the next generation of in-store experiences, bridging physical retail with digital capabilities through cutting-edge hardware, software, and AI. We partner with enterprise retailers to deliver seamless, high-scale integrations that power magical shopping experiences for millions of customers and thousands of stores. As a Senior Solution Architect, you will own end-to-end technical design and solutioning for our enterprise retail partners, serving as the primary technical liaison across Instacart Product and Engineering while collaborating closely with partner technology and business stakeholders. You’ll work on first-of-a-kind challenges in the in-store physical AI space, translating business needs into scalable architectures that launch successfully and stand the test of time. This role
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 are seeking a Senior Actuator Design and Integration Engineer to lead the development of custom electromechanical actuators for advanced robotic systems. You will own actuator development from early architecture and concept generation through prototype validation and system integration, partnering closely with mechanical, electrical, controls, firmware, reliability, and manufacturing teams. This role focuses on the design, integration, and validation of precision electromechanical systems, including motors, transmissions, sensing, structural components, and thermal architectures. You will help drive actuator development across the full engineering lifecycle while establishing scalable design, test, and integration practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the architecture, design, and integration of custom robotic actuators, including motors, transmissions, sensing, thermal systems, structural components, and packaging. Define actuator requirements and system-level trade studies around torque density, bandwidth, efficiency, thermal performance, backdrivability, inertia, reliability, manufacturability, and cost. Design precision electromechanical assemblies with strong attention to tolerances, alignment, load paths, thermal expansion, sealing, wear, and serviceability. Drive actuator integration into robotic systems, partnering closely with controls, firmware, electrical, and robotics software teams to optimize closed-loop pe
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 are seeking a Senior Mechanical Engineer to lead the design, integration, and sustaining engineering of mechanical subsystems in robotic platforms. You will work closely with experienced engineers and cross-functional partners to set functional requirements, develop and iterate on hardware to meet program expectations. This role is aimed at candidates with strong fundamentals in mechanical system design — including tolerance, alignment, load paths, wear, and failure modes — and robotics. You will contribute to real hardware programs moving from prototype through early production. You will lead both new subsystem development and ongoing improvements to existing systems based on testing, field performance, and manufacturing feedback. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the design and iteration of mechanical subsystems, including structures, mechanisms, and actuators. Create and maintain CAD models, assemblies, and drawings with appropriate tolerancing and documentation. Build and test prototypes, supporting debugging of mechanical issues such as fit, alignment, friction, and wear. Assist in developing test methods and executing validation to evaluate performance, durability, and failure modes. Work with cross-functional teams to integrate mechanical components with sensors, actuators, and control systems. Support transition of designs from prototype to manufacturable assemblies, incorporating DFM and DFA considerations. Collaborate with manufacturing partners
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 As a hands-on senior leader for our India SecOps team, you will shape and safeguard Everpure’s security posture at the intersection of detection engineering, threat hunting, attack surface management, and incident response. Positioned as a strategic cornerstone in Bangalore, you will empower an elite engineering team, optimize critical SecOps pipelines, and partner cross-functionally across global engineering and infrastructure groups. By driving execution excellence and high team morale, you ensure our enterprise platform and global telemetry remain resilient against evolving threats. WHAT YOU'LL DO Scale & Lead SecOps Operations: Architect, mentor, and grow the India SecOps team to foster an environment of high morale, technical excellence, and rapid execution across detection engineering and incident response. Proactively Manage & Remediate Attack Surface: Own end-to-end Attack Surface Management (ASM) across cloud environments, SaaS applications, endpoints, and secrets management to measurably minimize enterprise exposure and mitigate risk. Optimize Telemetry & Incident Response: Mature SIEM and SOAR automation pipelines to drastically reduce mean time to detect, contain, and respond (MTTD/MTTC/MTTR) while continuously elevating alert fidelity and signal confidence. Drive Cross-Functional Alignment & RCA Postmortems: Lead continuous validation through purple-teaming and incident postmortems alo
Power and Performance Validation Engineer About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debug compl
About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to senior leadership within Architecture and Validation, the Debug Validation Lead will drive post-silicon debug and validation activities for next-generation AI compute silicon and systems. The role is responsible for leading teams focused on identifying, reproducing, analysing and resolving complex silicon, firmware and system-level issues during bring-up, characterization and product readiness. This position combines deep technical debugging expertise with strong cross-functional collaboration across multiple engineering disciplines. The role will work closely with architecture, RTL, firmware, software and systems teams to improve debug methodologies, accelerate issue resolution and strengthen validation coverage. The role will work closely with architecture, RTL, firmware, software, systems and platform teams to improve debug methodologies, accelerate issue resolution and strengthen validation coverage. The Team The Post-Silicon Debug and Validation team sits within the Architecture and Validation organisation and is responsible for bring-up, debug and validation of Graphcore silicon and systems. The
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