Systems Research Engineer Intern Jobs

Position Overview Our customers are at the forefront of some of the most interesting data in the world, using SingleStore to push the boundaries every day. To do this well, they leverage the expertise of our Support Engineering Team, composed of technical subject matter experts on the frontlines of critical customer issues. This Support Engineering role skews far more towards engineering than typical technical support as you will need to delve into database internals and memory allocators, investigate Linux and host-related configurations, and diagnose SQL query behavior, all in the name of resolving complex database issues. Our Support Engineers are constantly learning a wide range of customer systems and technical concepts and are thrilled by the new and exciting challenges that they encounter on a regular basis. To accurately identify the source and solution of an issue, this team will take the time to learn about the customer’s business and systems while helping to improve their fundamental SingleStore and database operational knowledge. This often requires additional research and time spent on learning new technologies and tools outside of SingleStore while also being deeply engaged with multiple departments including development teams, query performance engineering, product management, infrastructure SREs, etc. Required Hours: Monday to Friday US West Coast (09:00 AM - 06:00 PM PST) What you'll do: Provide email and live technical support to our enterprise customers, acting as the first line of defense for complex technical issues, bug diagnosis, or resolving critical outages. Identify and reproduce product issues, perform QA, and submit formal bug reports or feature requests to the appropriate Engineering team. Collaborate closely with software developers, sales engineers, and technical account managers to keep all teams up to date with current issues a customer may be facing. Work to streamline and improve various Support and Engineering processes and tools,

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 As Claude's capabilities grow, so does our responsibility to ensure those capabilities reach the right people. The Access Programs team builds the systems that verify who our customers are, grant access to advanced model capabilities for approved use cases, and ensure that access is not misused. As a software engineer on this team, you will build the identity, vetting, and access management infrastructure that underpins our trusted access programs, along with the monitoring and enforcement tooling that keeps them safe. This work sits at the center of how Anthropic deploys frontier capabilities responsibly, balancing broad access with rigorous safeguards. Responsibilities: Build identity verification and vetting systems (KYC/KYB) that establish who our individual and business customers are Design and implement access control systems that grant, scope, and revoke access to advanced capabilities based on approved use cases Build infrastructure to configure safety systems and detection thresholds on a per-customer basis for trusted access programs Develop monitoring to detect misuse of expanded access, and tooling that enables enforcement teams to act on it Partner closely with policy, enforcement, threat intelligence, product, research, and go-to-market teams so that access decisions are well-informed and consistently applied Build systems that identify account compromise and takeover, apply mitigations in real time, and carry affected accounts through to full remediation Design and build the dashboards, alerting, and internal admin tooling that give the team and its partners clear visibility into the health and outcomes o

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 We are looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies. Responsibilities: Develop monitoring systems to detect unwanted behaviors from our API partners and potentially take automated enforcement actions; surface these in internal dashboards to analysts for manual review Build abuse detection mechanisms and infrastructure Surface abuse patterns to our research teams to harden models at the training stage Build robust and reliable multi-layered defenses for real-time improvement of safety mechanisms that work at scale You may be a good fit if you have: A Bachelor’s degree in Computer Science, Software Engineering or comparable experience Proficiency in Python and Typescript An ability to work across the stack Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also: 8+ years of experience in a software engineering position Have experience with integrity, spam, fraud, or abuse detection and mitigation Have experience building trust and safety detection mechanisms and intervention for AI/ML systems Have experience with prompt engineering, jailbreak attacks, and other adversarial inputs Have worked

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Metronome is a usage-based billing platform and a Stripe product. It helps modern software companies launch products faster, offer flexible pricing models, and streamline finance workflows. The Metronome Integration Engineering team sits at the intersection of sales, growth, product, and research and development. We own the technical aspects of the customer lifecycle after a sale and before the customer transitions to our post-implementation teams. What you'll do As an Integration Engineer, you’ll help customers implement Metronome successfully and realize value quickly. You’ll lead technical work across requirements gathering, solution and integration design, configuration, testing, data migration, launch, and handoff. Responsibilities Conduct discovery and scoping to understand customers’ challenges across billing, product launches, pricing and packaging, quote-to-cash, customer experience, and related areas. Support customers throughout the implementation lifecycle, including requirements gathering, technical design, integration design, testing, data migration, and launch. Provide expert guidance on usage-based pricing and consumption-based business models. Configure Metronome’s platform on behalf of customers. Design integrations between Metronome’s APIs and customers’ business systems—including CRM and CPQ platforms, payment and tax systems, ERP and billing providers, and reporting and analytics tools—in alignment with Metronome bes

About Formation Bio Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, John Doerr, Spark Capital, SV Angel Growth, and others. You can read more at the following links: Our Vision for AI in Pharma Our Current Drug Portfolio Our Technology & Platform At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently. About the Position As a Senior Site Reliability Engineer at Formation Bio, you will build and operate the infrastructure, delivery systems, and operational practices that allow our engineering organization to ship reliable software quickly and safely. You will work across cloud infrastructure, developer platforms, observability, and production workloads, including product applications, internal tools, data systems, and ML and AI workloads, taking problems from initial diagnosis through implementation and production adoption. Formation Bio is an AI-native engineering

SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter , LinkedIn , Facebook and Instagram . Position Summary We are hiring a Software Dev Engineer to design, build, test, and deploy AI-powered applications. You will work across the full application lifecycle — from architecture and implementation through automated testing, CI/CD deployment, and production monitoring — building features that put large language models and agentic tooling to work inside SonicWall's internal systems. This is a hands-on engineering role for someone with 6–8 years of professional software development experience who is comfortable owning services end to end: writing production-quality code, integrating LLM and agentic APIs, standing up reliable data and retrieval pipelines, and shipping through a disciplined test-and-release process. You will collaborate closely with senior engineers, product stakeholders, and platform teams to turn requirements into dependable, well-tested applications. Key Responsibilities Develop AI applications: Design and build features and services that use LLM and agentic capabilities — prompting, tool/function calling, retrieval-augmented generation (RAG

About the Team The Emerging Products team is a lean, high-output product lab group that builds products at the forefront of model capabilities. We collaborate across all teams within the company, from research and infrastructure to consumer products. The team is responsible for identifying new product opportunities, building them quickly, dogfooding them internally, and then launching the successful products to users. We use data, user research, and analytics to inform our ideas, and make decisions on what experiments are worth iterating, stopping, or scaling. About the Role We’re looking for a senior, product-minded software engineer to own ambiguous 0-to-1 work from idea through prototype, validation, and handoff. This is a full-stack role with a strong frontend and product emphasis: you will build the interfaces and supporting backend systems needed to test new experiences quickly, while making sound architectural choices that enable successful concepts to scale. This role is based in our Mission Bay office in San Francisco. In this role, you will: Build and ship high-quality, product experiments across the full stack. Turn ambiguous user needs and emerging technical capabilities into testable product concepts, using research and metrics to guide iteration. Own technical direction for 0-to-1 projects, balancing speed, reliability, and a clear path from prototype to scalable product. Partner closely with design, product, research, and engineering teams to dogfood, evaluate, launch, and transition successful experiments. You might thrive in this role if you: Have a track record of building and shipping end-to-end products in fast-moving, startup, founder-led, growth, or other high-ownership environments. Bring strong frontend engineering skills and enough backend and systems depth to make sound full-stack architectural decisions. Pair product intuition with evidence, using user research and product data to identify opportunities and make pragmatic tradeoffs. Operat

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 mission is to create reliable, interpretable, and steerable AI systems. We believe powerful AI can compress a century of scientific progress into a decade. Claude Science is a big part of building toward that future. Claude Science is an AI workbench that gives researchers a single environment for work that today spans dozens of disconnected tools — literature, specialized databases, scientific computing, analysis, and publication-ready outputs. Claude Science already renders protein structures, genome tracks, and chemical structures natively, and coordinates multi-agent workflows with built-in review for citation and calculation errors — and we’re just getting started. Much of this is being built 0→1 right now: you’ll shape both the product and the architecture in a category no one has defined yet. You'll be a technical leader who thinks holistically about the end-to-end researcher experience, partners directly with our internal research team to push model capabilities into production, and carries real ownership over what we ship next. Our north star is accelerating scientific progress — across biology, chemistry, physics, and beyond — from early discovery through real-world application, by an order of magnitude. This work supports programs like Anthropic’s AI for Science Program and our rare disease research grants . What you'll do Ship fast against a roadmap you help shape: this is a product in a category no one has defined yet, and the highest-leverage problems are still unclaimed Interface directly with working scientists — academic labs, industry R&D teams, and research institutes — during key conv

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 We're hiring Cyber Evaluations Engineers to build and run the evaluations that measure cyber-relevant capabilities and safeguard robustness in our models. You'll design new evals, run per-release robustness testing, and dig into data on jailbreaks and prompt bypasses to understand where our safeguards hold up and where they don't. You'll also design many of the probes that detect cyber abuse in production and help shape the overall detection architecture alongside the policy team. Key responsibilities Design and run capability, uplift, and safety evaluations to assess cyber-relevant risk in new models Execute per-release safeguard-robustness testing ahead of major model launches Analyze evaluation results and communicate findings clearly to the team and to stakeholders Design, prototype, and tune detection probes for cyber misuse Work with the cyber policy team to turn policy lines into a layered, robust abuse-detection architecture, and measure its precision and coverage over time Build and maintain internal tooling used to run and score evaluations Collaborate with policy and engineering partners to translate eval findings into safeguard improvements Minimum qualifications Experience building or running evaluations, benchmarks, or test suites for software or ML systems, including delivering results on short, fixed timelines Hands-on cybersecurity experience (e.g., CTF participation, vulnerability research, exploit development, or security research) Proficiency in Python Strong ability to communicate evaluation results with multiple cross-functional stakeholders or potential policy stakeholders Preferred qualific

Job Details: Job Description: Join Intel-and build a better tomorrow. Intel creates an environment where employees can prosper while creating the innovative technologies that make amazing possible. As a Facilities Operations ,our scope is vast and includes operating and maintaining all Intel sites, offices, labs, data centers and factories globally as well as onsite services and experiences that help employees stay safe and productive. Our Mechanical Engineers make a big impact by supporting our daily tactical efforts in safety, reliability, and environmental objectives. The Role and Impact As a Facilities Mechanical Engineer, you will play a critical role in ensuring the availability, reliability, and maintenance of mechanical systems (Oil Free Air, HVAC, Exhaust, Process Vacuum, PCW, Wet system, Fire Life Safety System and etc) essential to Intel's manufacturing, clean room, and research and development activities. You'll focus on designing, maintaining, and troubleshooting mechanical systems to support daily operations, system reliability, safety and environmental objectives. Your expertise will directly contribute to maintaining optimal operational performance across Intel's facilities. Key Responsibilities - Own, sustain, and improve system reliability, capability, capacity, operational troubleshooting, system upgrade evaluation and optimization of mechanical systems. - Develop engineering scopes of work for mechanical projects and conduct design reviews and evaluations. - Partner with internal customers and external service providers to ensure systems are maintained and operated within specified limits. - Support environmental compliance for facilities mechanical systems, ensuring adherence to safety and reliability standards. Compliance to EHS / regulatory / insurance audit requirements (Fire protection / Life safety system) - Conduct feasibility studies

About the Team OpenAI's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. The API Platform turns frontier research into reliable capabilities that developers use to build transformative products and services for people around the world. API Safety's goal is to ensure safe deployment of frontier models in the API. We design APIs and systems that help developers share usage context, understand safety events, and apply safeguards tailored to the risk profile of the applications they are building. This work is critical to our frontier model launches and partners closely with teams across API, Integrity, and Safety Research. About the Role We're looking for product-minded software engineers to join a team that is addressing emerging risks at the frontier of model development while building novel solutions for real-world AI deployment. The day-to-day work ranges from solving production challenges to designing new product experiences and safeguards. The right candidate is comfortable balancing tradeoffs across developer experience, latency, reliability, and risk. In this role, you will: Design and build dashboards and APIs for safety controls and customer-facing observability. Develop scalable systems that extend trusted safety capabilities to new use cases, customers, and deployment environments. Partner with Safety Research and Integrity to build safeguards that mitigate emerging risks. Be responsible for the availability, latency, and scalability of safeguards across high-volume API traffic. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed systems. Strong s

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 We build and run the secure execution environment behind Claude's agentic capabilities. When Claude writes and runs code, browses the web, or uses a computer, that happens on infrastructure our team owns. We work at the intersection of systems engineering and security. The goal is to make untrusted code execution safe, fast, and reliable enough that product teams don't have to think about it. This is the layer between the model and the outside world, and it has to hold up at scale for every Anthropic product. We're hiring engineers who have experience building for containerized workloads and have a keen eye for building products used by millions of customers. What you'll do You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent distributed systems, cloud-native products, developer tools, or external developer facing products Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end Are proficient in Python, Go,

About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. Our team builds the software, tooling, and operational systems that help manage this fleet at scale. We work across production engineering, distributed systems, capacity management, and operational automation to improve reliability, reduce manual work, and make better use of available compute. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will develop the systems that help manage the GPU fleet powering ChatGPT, including tooling for fleet health, capacity planning, operational automation, and incident response. You will work closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and compute utilization. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build software and internal tools to manage large-scale GPU infrastructure supporting ChatGPT inference. Develop systems for capacity planning, fleet health monitoring, and resource utilization. Automate operational workflows, including incident detection, diagnosis, and response. Identify and address bottlenecks affecting fleet reliability, scalability, and performance. Partner with infrastructure, research, and product engineering teams to improve the compute platform. You Might Thrive in This Role If You Have experience operating large-scale production infrastructure, GPU clusters, or other compute-intensive distributed systems. Have a background in production engineering, site reliability engineering, infrastructure engineering, or platform engineering. Have built software that automates operational workflows and reduces manual work. Have worked with distributed infrastructure, cluster orchestration, or large-scale int

Req: FEQ227R196 Location: Tokyo, Japan Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.)

About Graphcore 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 Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal t