Systems Research Engineer Intern Jobs

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our search efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. 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. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluating, and integ

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. About the Role We're looking for technically curious, customer-focused System Verification Engineers to join our System Quality Assurance team. You'll validate and evaluate how UniFi products work together and how customers experience them - from first-time setup to everyday use across devices, web and mobile applications, and cloud services - and your read on that experience helps decide what's ready to ship. We're looking for someone with good judgment, an eye for detail, and a real understanding of what makes a product intuitive and well designed. You should be able to spot a confusing experience, explain why it's confusing, and work effectively with engineering and design teams around the world to fix it. Along the way, you'll gain hands-on experience with real hardware, run performance experiments, analyze data, and help bring products to market with best-in-class reliability. Curiosity, clear communication, and a willingness to learn are essential here; automation is a plus. Responsibilities Test complete customer workflows across the UniFi ecosystem, including Network, Protect, Access, Connect, UniFi OS, and Site Manager. Check that every product works together and feels consistent to the people using it. Evaluate setup, device adoption, navigation, everyday management, and recovery flows through the eyes of both administr

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. About the Role We're looking for technically curious, customer-focused System Verification Engineers to join our System Quality Assurance team. You'll validate and evaluate how UniFi products work together and how customers experience them - from first-time setup to everyday use across devices, web and mobile applications, and cloud services - and your read on that experience helps decide what's ready to ship. We're looking for someone with good judgment, an eye for detail, and a real understanding of what makes a product intuitive and well designed. You should be able to spot a confusing experience, explain why it's confusing, and work effectively with engineering and design teams around the world to fix it. Along the way, you'll gain hands-on experience with real hardware, run performance experiments, analyze data, and help bring products to market with best-in-class reliability. Curiosity, clear communication, and a willingness to learn are essential here; automation is a plus. Responsibilities Test complete customer workflows across the UniFi ecosystem, including Network, Protect, Access, Connect, UniFi OS, and Site Manager. Check that every product works together and feels consistent to the people using it. Evaluate setup, device adoption, navigation, everyday management, and recovery flows through the eyes of both administr

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Responsibilities Lead hardware circuit design, schematic development, and PCB layout review to ensure robust system performance and manufacturability Drive design verification, system bring-up, debugging, and root cause analysis, including RMA failure resolution Own BOM management and support production to ensure smooth transition from NPI to mass production Evaluate and integrate new technologies, components, and platforms to enhance product competitiveness Participate across the full product lifecycle from NPI, MP to EOL Collaborate with cross-functional teams including layout, component engineering, firmware, mechanical, power, thermal, QA, software, PM, ID, and compliance Qualifications Bachelor’s degree or above in Electrical Engineering or a related field 5+ years of hands-on experience in system-level hardware design Experience with networking products such as Ethernet gateway, switch, or NAS platforms Solid understanding of Ethernet technologies including 802.3 PoE (PSE/PD), 1G/10G PHY, and switching or routing fundamentals Experience in hardware validation, debugging, and failure analysis in production environments Familiarity with compliance requirements including ESD, surge protection, and safety standards Proficiency in hardware design tools such as OrCAD Capture, Cadence Allegro, or Mentor PADS Nice to Have Experienc

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? At Fin you'll be a Systems Engineer in IT, working on evolving our IT infrastructure with a focus on deliverability, identity & access management and compliance. This is a great opportunity to join an ambitious AI-native IT team that leverages SaaS-based solutions to be at the forefront of business process and employee lifecycle automation. If you're coming from a traditional systems engineering or DevOps background, this role will expand the scope of your experience to truly agile, modern cloud environments. If you're already in the identity management and employee lifecycle automation space, this is the chance to take an ambitious next step in your career and be part of an engineering organisation that is scaling at incredible speed. What will I be doing? Build and own automations.

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 Robotics Control Systems Engineer to take on a foundational role within our robotics team. You’ll help architect, implement, tune, and verify the control infrastructure that enables intelligent, reliable, and responsive robot behavior. This is a deeply hands-on role focused on real-time systems, actuation, dynamics, low-level hardware interaction, and whole-robot performance. You’ll spend significant time working directly with robots onsite: debugging behavior, tuning subsystems, running experiments, and providing feedback across mechanical, electrical, and software teams. This role is based in San Francisco, CA, and requires in-person 5 days a week. In this role, you will: Design and implement real-time control algorithms for robotic systems, including motion control, feedback loops, state estimation, actuator control, and subsystem tuning. Define the control architecture from low-level actuators and hardware interfaces through whole-robot behavior and policy. Identify and characterize actuator, hardware, and software parameters through rigorous experimentation, testing, commissioning, and verification. Work with machine learning engineers to implement reinforcement learning models. Collaborate across mechanical, electrical, and software teams to integrate control logic with sensing and actuation hardware. Help inform the mechanical and electrical design to maximize capability and flexibility. Create the control system architecture; determine the correct level of abstraction from actuators all the way up to whole-robot

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? At Fin you’ll be a Systems Engineer in IT, you will work on evolving our IT infrastructure with a focus on deliverability, identity & access management and compliance. This is a great opportunity to join an ambitious IT team that leverages SaaS-based solutions to be at the forefront in the business processes and employee lifecycle automation space. If you are coming from a traditional systems engineering or dev ops background, this role will expand the scope of your experience to truly agile, cutting edge, cloud environments. If you are already in the identity management and employee lifecycle automation space, this is the chance to take an ambitious next step in your career and be part of an engineering organisation that is scaling at incredible speed. What will I be doing? Identify and solve team, organisational, and business automation and integration problems. Design, build, and own efficient and easy-to-maintain automations and integratio

About the Team The OpenAI 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 As a Software Engineer, Distributed Data Systems, you will design, build, and operate some of the largest distributed data systems in the world. You will be responsible for the end-to-end stack to deliver and consume top-quality data for robotics training at exabyte-scale. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI’s rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable, large-scale systems in high-stakes environments. 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. In this role, you will: Design, build, and maintain data infrastructure such as exabyte-scale distributed data processing, data selection, automated labeling, and training data loaders. Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient. Partner with researchers to deeply understand requirements and translate them into production-ready systems. Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. Deliver the best possible data for training robotics models. You might thrive in this role if you: Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. Are detail-oriented a

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. Note: we don't have open Research Manager positions on the Interpretability team at this time. However, we're actively growing our team of Research Engineers and Research Scientists . If you're excited about interpretability research and open to an individual contributor role, we encourage you to apply. About the Interpretability team When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks, or as treating neural networks as binary computer programs we're trying to "reverse engineer". We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our vision post ). We have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work which f

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As a core technical leader within our Agentic AI initiatives, you will shape the vision, architecture, and execution of Dialpad’s next-generation AI platform, moving the industry beyond passive copilots into autonomous workflow execution. Working closely with Product, Applied Research, Design, and executive leadership,

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

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 role Anthropic's research teams are pushing the boundaries of AI safety and capability research, and they need exceptional tools to do their best work. As a Software Engineer on the Research Tools team, you'll build the infrastructure and applications that enable our researchers to iterate quickly, run complex experiments, and extract insights from frontier AI systems. This role sits at the intersection of product thinking and full-stack engineering. You'll work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you're building human feedback interfaces for model evaluation, creating platforms for experiment orchestration, or developing novel visualization tools for understanding model behavior, your work will directly accelerate our mission to build safe, reliable AI systems. We're looking for someone who can operate with high agency in an ambiguous environment—someone who can be dropped into a research team, quickly develop domain expertise, and independently drive impactful projects from conception to delivery. No ML or Research experience is required Responsibilities Build and maintain full-stack applications and infrastructure that researchers use daily to conduct experiments, collect feedback, and analyze results Partner closely with research teams to understand their workflows, pain points, and requirements, translating these into technical solutions Design intuitive interfaces and abstractions that make complex research tasks accessible and efficient Create reusable platforms and tools that accelerate

Job ID: 111265 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Responsibilities: Maintain and document current and new system requirements. Perform Server Administration tasks, including user and group administration, research event logs to continually improve service for end users. Work with product, engineering, and operational business stakeholders to understand and prioritize business system’s needs. Monitor infrastructure and platform performance. Create architectural designs that enhance resilience and promote business continuity. Manage the deployment of new software, version upgrades, patch releases and major incidents. Manage development, test, release, and production environments in Cloud. Identify actionable, value-added optimization and efficiency opportunities, and contribute to the continuous improvement of applications and processes. Manage stakeholder requirements and develop detailed implementation plans. Employ agile methodology in the development of software, systems interfaces, and application configurations. Experience: Education and Experience: Master's degree or foreign equivalent in Computer Science, Engineering, or related field. 2 years of experience in job offered, software development, or related occupation. Skills: Experience with IT systems and Business Systems Oracle Fusion cloud. Experience with Oracle Cloud ERP and Boundary apps. Experience with SQL, PL/SQL, BI, OTBI, and BICC reports. Experience with Oracle finance and Source Code Management (SCM). Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid tim

About the Team OpenAI Consumer Devices is building the next generation of products that bring powerful AI into people’s everyday lives. Guided by OpenAI’s mission to ensure AGI benefits all of humanity, our team combines world-class researchers, engineers, designers, and operators who care deeply about creating useful, intuitive, and responsible technology. You’ll have the opportunity to work alongside exceptional people on ambitious, zero-to-one challenges at the intersection of hardware, software, and AI. This is a chance to help define an entirely new category of products—and shape how people experience AI in the future. Our team works across silicon, embedded systems, operating systems, and cloud services to build reliable consumer devices and the novel platforms required to support them. We partner closely with research to bring advanced AI capabilities into the physical world. About the Role As an Operating Systems Engineer focused on on-device inference, you will design, develop, and ship the OS stack that makes advanced AI capabilities reliable, responsive, and energy efficient on consumer devices. Your work will span OS services and frameworks, inference runtime integration, model fitting, scheduling, and performance and power management. You’ll partner with research to adapt models to device constraints, make design decisions across the stack, and carry solutions from early exploration through integration and production. In this role, you will: Build the inference platform: Design and implement maintainable OS services, frameworks, and clear interfaces for inference execution, model loading and lifecycle, and resource management. Fit models to device constraints: Partner with researchers on quantization, runtime integration, and memory optimization to meet memory, compute, and energy budgets while evaluating model quality and product behavior. Coordinate system resources: Develop scheduling and resource policies that balance inference with other device act

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