System Engineering Intern in United States

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. This role sits at the center of cutting-edge AI hardware development, keeping the servers, PCIe systems, and engineering infrastructure running that power next-generation compute. You’ll be hands-on with rapidly evolving prototype and production systems, installing, maintaining, and troubleshooting hardware in fast-paced R&D and data center environments. Acting as a critical bridge between hardware engineers, software teams, and IT, you’ll help ensure seamless access to the platforms that turn ideas into working silicon and systems. This role is onsite, based out of Toronto, Canada or Austin, Texas. 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 A hands-on hardware professional who enjoys building, maintaining, and troubleshooting complex computing systems. Comfortable working in fast-paced R&D environments where hardware, firmware, and software are constantly evolving. Knowledgeable in computer architecture, operating systems, and hardware diagnostics, with strong problem-solving skills. Collaborative, detail-oriented, and motivated to improve processes through documentation, scripting, and automation. What We Need Inst

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is about empowering enterprises to achieve their full potential, and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology, and careers, to the next level. About the Role The Cortex Code team is building the future of coding agents for working with data. See our flagship product in action: Cortex Code in Action: Live Demos + AMA . Your work will directly impact how developers and businesses build with data. You'll own the full AI engineering lifecycle: design, prompt/tool engineering, evals, deployment, measurement, and optimization. You'll work with a small, high-powered modeling and infrastructure team. What you will do in this role: Own features end-to-end for Snowflake Cortex Code products. Build agentic workflows, coding harnesses, evaluation pipelines. Build enterprise-grade context engineering: function calling, tool schemas, guardrails, agent teams, and verification/repair. Partner with product and infra: translate customer problems into products and experiments. Collaborate with infrastructure teams to productionize improvements. Work with an elite team of engineers towards building great products Requirements: Bachelor’s degree in Computer Scienc

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Advanced Engineer, Power System Controls plays a key role in the design, development, and implementation of control software for Hyliion’s Karno Power Module. This position focuses on systems involving combustion, thermal management, pressure regulation, high-voltage, and power management. The engineer will be responsible for developing and validating control algorithms, tuning system parameters, and analyzing data to ensure performance meets engineering specifications. Additional responsibilities include preparing technical documentation, supporting root cause analysis, and ensuring timely, high-quality software delivery. The role requires cross-functional collaboration and occasional travel to support system testing and troubleshooting. Duties and Responsibilities Design, develop, and implement high-quality control software for Hyliion’s Karno Power Module, which includes combustion, thermal, pressure, high-voltage and power management systems. Define and conduct tests to verify software and tune control parameters to meet key performance indicators. Prepare reports and technical documentation related to system performance, control strategies, and compliance. Process and analyze data to verify software against engineering specifications, support root cause analysis and for optimizing performance. Ensure on time delivery with quality. Assist product team in defining customer requirements and generate corresponding engineering specifications. Qualifications Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Qualifications include: Education, Experience and Cert

Electronic System Design and Analysis Engineer (Experienced or Senior) Company: The Boeing Company The Boeing Test Operations and Engineering (TO&E) team in Berkeley , Missouri is seeking an Electronic System Design and Analysis Engineer to join our Instrumentation Installation Design group to support all major programs in the St. Louis area. We are currently hiring for a broad range of experience levels including Experienced and Senior Electronic System Design and Analysis Engineers. Position Responsibilities: Electrical Design & Testing AC and DC power applications Assisting shop with build information Reading electrical drawings/schematics Troubleshooting Electrical component/wiring faults Production Functional and Environmental Acceptance Testing Designing new test sets for various weapon and aircraft electronics Performs system tests to verify operational and functional requirements Supports resolution of product integration issues and production anomalies Researches basic technologies for potential application to company business needs Assists in monitoring suppliers' performance to ensure compliance with requirements Develops or modifies basic hardware and software designs based on defined requirements Assists with the development and documentation of electronic and electrical system requirements This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location options. Basic Qualifications (Required Skill/Experience): <

Job Details: Job Description: The Role and Impact As a GPU Platform Hardware Design Engineer, you will play a pivotal role in designing and developing high-quality GPU hardware platforms that drive innovation in high-performance computing, graphics, and visualization technologies. You will lead the design process from initial feasibility studies through board layout, tapeout, and platform power-on, ensuring robust functionality and compatibility with industry standards. Your expertise in platform-level requirements, electrical engineering applications, and system bring-up will directly contribute to delivering cutting-edge GPU systems that accelerate Intel's leadership in computing. Business group The Data Center Group (DCG) is dedicated to advancing Intel's role in powering the digital world with leading-edge technologies. Focused on delivering innovative solutions for data center and cloud environments, DCG supports high-performance computing and graphics to enable capabilities such as AI, machine learning, and advanced visualizations. As part of the GPU IP Engineering team within DCG, you'll contribute to developing GPU systems that meet the evolving demands of the industry while supporting Intel's broader mission to create world-changing technology. Key Responsibilities - Design, develop, and evaluate electronic components, PCBs, and integrated circuits for GPU hardware platforms. - Translate platform-level requirements into detailed specifications and ensure adherence throughout the design process. - Define component placement and trace routing rules to optimize board layouts for performance, power, and signal integrity. - Conduct feasibility studies, board layout, tapeout, and platform power-on activities. - Perform functionality tests and utilize tools to verify platform configurations and compatibility. - Research, develop, and validate firmware, hardwa

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 &#34;flight recorder&#34; 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 &#34;Hardware Fault,&#34; &#34;Software Bug,&#34; or &#34;Environment Issue.&#34; This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define &#34;signals of impending failure,&#34; 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&#43; years in systems programming. Experience building automated

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. Measure, re

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We're looking for a Director of Engineering to join our leadership team in the AI Functions product portfolio, a hybrid director/principal engineer role at the forefront of AI-powered analytics. Our mission is to democratize AI by surfacing powerful AI functions directly in SQL for analyzing structured and unstructured data, with minimal configuration. We handle the full AI lifecycle behind the scenes, so data analysts, engineers, and scientists can build data transformation pipelines with AI using the most sophisticated building blocks seamlessly within their existing SQL workflows. The AI Functions product portfolio represents one of the most strategic and impactful product surfaces within Snowflake, bringing together two of the company's core strengths: its industry-leading ability to process massive volumes of data and its growing capability to make that data AI-ready. By embedding advanced AI and LLM-powered functions directly into SQL, this portfolio transforms Snowflake from a data platform into an intelligent data system where structured and unstructured data can be seamlessly prepared, enriched, and analyzed using AI at scale. This convergence enables customers to operationalize AI within their existing workflows, unlocking faster insights, more powerful applicatio

The Engineering Lead Analyst – SonarQube & Code Quality Engineering is a senior-level engineering role responsible for leading static code analysis, automated code quality governance, security vulnerability remediation, and AI-augmented developer enablement across enterprise software delivery pipelines. In this role, you will champion software reliability, maintainability, clean-coding standards, and automated quality gates. You will partner with development teams, system architects, and platform engineering to integrate and manage enterprise-scale code quality platforms (such as SonarQube) both on-premises and in cloud/SaaS environments. Additionally, you will drive modern engineering practices by embedding Behavior-Driven Development (BDD) within your own software delivery and leveraging Agentic AI workers and Model Context Protocol (MCP) architectures to optimize developer experience, streamline code governance, and boost engineering velocity. Key Responsibilities 1. Code Quality & Static Analysis Platform Ownership Lead the architecture, deployment, administration, and continuous enhancement of enterprise Static Application Security Testing (SAST) and Code Quality platforms (e.g., SonarQube , DeepSource, Codacy, Semgrep). Configure, calibrate, and enforce automated Quality Gates, code rulesets, technical debt calculation models, and code-coverage baselines across multi-language enterprise repositories. Oversee version upgrades, patching, high availability, and operational maintenance for on-premises and SaaS/cloud-hosted code quality infrastructure. 2. CI/CD & Pipeline Integration <li style=

Manufacturing Test Engineering Manager Position Summary We are seeking an experienced Manufacturing Test Engineering Manager to lead the development and execution of the end-to-end manufacturing test strategy for next-generation AI server platforms and datacenter infrastructure. This role is responsible for defining and driving the manufacturing test architecture from L6 board assembly through L11 rack-level integration and final system validation , ensuring world-class product quality, manufacturability, and production scalability. This leader will manage a team of 3–5 Manufacturing Test Engineers while partnering closely with Hardware, Firmware, Platform, Validation, Quality, Operations, and Joint Design Manufacturing (JDM) partners. The role owns the manufacturing test strategy, test coverage, factory test infrastructure, manufacturing capacity planning, and continuous improvement of manufacturing quality. Key Responsibilities Manufacturing Test Strategy Define and own the end-to-end manufacturing test strategy from L6 board assembly through L11 rack integration . Develop standardized manufacturing test methodologies that optimize quality, throughput, cost of test, and scalability across multiple products and JDM sites. Establish manufacturing test standards, best practices, and engineering processes that support high-volume server manufacturing. Technical Leadership & People Management Lead, mentor, and develop a team of 3–5 Manufacturing Test Engineers supporting multiple hardware programs. Establish team priorities, allocate resources, and ensure successful execution of manufacturing test deliverables. Foster a culture of technical excellence, accountability, collaboration, and continuous improvement. Serve as the primary technical escalation point for manufacturing test and production issues. Cross-Functional Engineering Collaboration Partner with Hardware, Platform, Firmware, Validation, Reliability, Quality, and Operations teams to ensure manufac

We are looking for a Senior System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response. What you'll be doing: Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow) Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes Drive upstream contributions to OVN-Kubernetes and related open-source projects Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure Drive reliability through incident management, resource monitoring, and performance tuning<

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: The Web Infrastructure team builds the foundations behind Notion’s web clients, including client architecture, performance, reliability, and shared design systems. As Engineering Manager, you’ll lead the team through the evolution from Notion Clients. You’ll set strategy, develop senior engineers and managers, and partner across Notion to make the product faster, more reliable, and easier to build. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: You'll build and manage a diverse and inclusive team of engineers and managers working on core parts of Notion's architecture. You'll create a healthy environment in your team that embodies Notion's values. You'll recruit, coach, and develop engineers. You'll ensure engineers are regularly receiving feedback and making progress on personal and professional goals. You'll facilitate planning—the prioritization, sequencing, and staffing of work—for your team. You'll be responsible

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Backend Engineer on the Chat Engine team, you'll build the engine behind GitLab Duo Chat, the conversational AI experience for GitLab. You'll work primarily in Python to build and maintain our agentic runtime: the Flow Registry, LangGraph flows, and the Duo Workflow Service. You'll also work in the GitLab Rails monolith, where Chat connects with the product. You'll own scoped parts of the system, ship small features and improvements with minimal guidance, and collaborate with the team on larger projects. You'll work alongside senior and staff engineers who will partner with you on design and support

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role AI and machine learning are reshaping how developers debug, monitor, and ship software, and Sentry is uniquely positioned to lead that shift. We sit on a novel and massive dataset of real production errors, spans, and logs from tens of thousands of engineering organizations — the kind of signal that makes ML genuinely useful, whether it's a clustering model that groups related issues, a ranking system that surfaces the right alert at the right time, or an agent that proposes a fix. We're looking for an Engineering Manager to lead and grow our Machine Learning Engineering team. This team owns the full spectrum of ML at Sentry: classical techniques like clustering, ranking, anomaly detection, and embeddings that quietly power core product surfaces today, alongside the LLM-based and agentic systems shaping where the product is headed. You'll partner closely with product, design, and engineering leaders to decide where ML belongs in our products, what kind of ML actually fits the problem, and how we translate that work into experiences millions of developers rely on every day. In this role you will Set technical direction across the team's full ML surface area — from classical models for clustering, ranking, and anomaly detection to LLM-based and agentic systems — and make sharp calls about which approach fits each problem Define how the team evaluates and monitors ML systems in production, from offline metrics to online experimentation to model and agent observability Stay hands-on enough to review code and model designs, contribute to architecture discussions, and unblock engineers on complex ML problems Define

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As an Engineering Manager, Git at GitLab, you’ll guide a deeply technical team focused on building, maintaining, and providing expertise on the Git version control system. The team’s work spans upstream development of Git, support for teams across GitLab, new tooling, scalability improvements, new data formats, and ongoing maintenance of the Git codebase. This role is a good fit for you if you can guide senior and staff engineers through complex, long-horizon technical work while building a culture of technical rigor, clear accountability, and ownership. You’ll help the team balance upstream open source d