System Engineering Intern in United States

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We're seeking an exceptional Staff Software Engineer to join our Observability team at Pinterest. This role combines deep technical expertise in distributed systems and data engineering with a product-oriented mindset to build world-class observability solutions that empower our engineering organization. As a Staff Engineer on the Observability team, you'll be responsible for designing and building the infrastructure and tools that provide visibility into Pinterest's large-scale distributed systems, helping thousands of engineers understand, debug, and optimize their services. What you'll do: Define and execute the observability roadmap, treating it as a product. Understand engineering team needs and translate them into technical solutions with measurable impact Architect, build, and scale distributed observability infrastructure (me

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

Ground Software Engineering Manager -Millennium Space Systems — USA - El Segundo, CA. Apply via Workday.

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a principal engineer on the Online Systems team, you’ll join a team that powers Pinterest’s most business-critical online systems at massive scale, driving the reliability, efficiency, and evolution behind every core Pinner and Advertiser experience. You'll lead major efforts like multi-region deployment and Kubernetes migration, set the standard for operational excellence, and define the long-term vision for our online serving infrastructure, supporting machine learning and product innovation across the company. This is an opportunity for high-impact technical leadership, broad visibility, and cross-functional influence at the heart of Pinterest’s platform. What you’ll do: Improve reliability, scalability and infra efficiency for Pinterest’s critical online systems across storage and caching, online service and realtime analytics syste

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The opportunity The Autonomous Freight Systems team is a brand new, AI-first engineering team in San Francisco. This team will own Flexport’s client-facing rates platform and the self-serve freight booking experience—two of the highest-leverage surfaces in our Client App that dictate how clients see pricing and book freight without manual intervention. As a Staff Engineer, you will be the technical anchor for our next-generation AI-powered rates platform. We aren't just building a UI; we are building AI agents that handle real logistics work: parsing complex rate sheets, managing pricing intelligence across ocean, air, and trucking, and making "Self-Serve" a reality for thousands of shippers. You will build the intelligence layer that allows clients to commit freight on technology alone, with no account executive and no operations touch. This is a ground-floor opportunity to shape technical direction, set up a new codebase, and build the platform that moves Flexport from an assisted-sales model to a tech-run one for the long tail of our client base. You will partner with Pricing, Sales, Ops, and Design on hard domain problems and ship to the most-used client

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

The Engineering Manager, Memberships leads the team responsible for building and operating Topgolf’s Memberships systems, from guest-facing membership experiences through the backend services that power them. This role owns the people, process, and delivery of the Memberships engineering team, while staying technically credible across a full stack built on Go, Vue.js, and PostgreSQL. Requirements Lead, grow, and manage a team of full-stack engineers building Memberships systems, including hiring, performance management, career development, and mentorship Set clear goals and expectations for the team, run effective 1:1s, and build a culture of ownership, accountability, and continuous improvement Balance workload and staffing across Memberships initiatives, escalating resourcing gaps and continuity risks early Guide architecture and design decisions across Memberships systems, drawing on full-stack experience spanning Go, Vue.js, PostgreSQL, and API design Set engineering standards and best practices for code quality, testing, and release processes, and stay close to the codebase through code reviews and hands-on problem solving on critical issues Own delivery of the Memberships roadmap end to end, from technical planning through implementation, QA, release, and post-launch monitoring, ensuring systems are observable, testable, secure, and built to scale with guest demand Partner with product, design, QA, and platform engineering to translate guest needs and business priorities into a clear, prioritized Memberships roadmap Represent the Memberships team in cross-functional planning and architecture discussions, communicating progress, risks, and tradeoffs to engineering leadership and business stakeholders Critical Skills Strong architectural judgment and the ability to balance technical debt, delivery speed, and long-term maintainability <

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary: We are looking for a Staff Systems Engineer - Digital to join our team, the foundational layer that powers access, governance, and intelligence across our digital products. You will work horizontally across engineering, product, and AI teams, leading, owning, and evolving the shared infrastructure that every team at the company depends on. You will be the primary authority on how information is modeled, governed, and served across operational, analytical, and AI workloads - driving quality, compliance, and reliability at scale. If you thrive in a role where your architecture decisions multiply the productivity and capability of entire teams, this is the opportunity for you. Key Responsibilities: Data Architecture & Platform Ownership: Define and own the enterprise data architecture strategy across operational, analytical, and AI/ML workloads Design and govern data models, data contracts, and canonical schemas used across product and platform teams Evaluate and standardize data platform tooling — data lakes, warehouses, streaming, and serving layers (GCP BigQuery, Pub/Sub, Dataflow, or equivalent) Serve as the primary point of contact and SME for shared data platform concerns acro

NVIDIA’s EDA Infrastructure organization builds and operates the systems that support chip development. We are looking for an engineering manager to lead the team responsible for operational processes and platforms across incident management, maintenance, on-call, issue management, and customer-serving readiness. You will own the roadmap and delivery, from defining how teams work to building the tools they use. You will partner with infrastructure and service owners to improve reliability, reduce manual work, and ensure services are ready to support customers. Your team will use automation, AI, and lessons from operational events to drive improvements. What you’ll be doing: Lead a team and own the roadmap for operational processes and platforms, from requirements and delivery through adoption and results. Set technical direction, prioritize work, and guide execution across engineering and operational disciplines. Partner with infrastructure, product, and security teams to establish consistent practices for incident response, maintenance, on-call, issue management, and customer-serving readiness. Hire and develop engineers and technical leads, building a team with clear ownership and accountability. Align priorities across teams, communicate progress and risks, and provide technical leadership during major incidents. What we need to see: <span style="co

About the Team The ChatGPT Search Product Infrastructure team builds the foundational systems that power search experiences across ChatGPT. We develop the product infrastructure that connects models with search systems and other sources of real-time information, enabling ChatGPT to deliver timely, relevant, and trustworthy answers to users around the world. Our work sits at the intersection of product engineering, AI, and large-scale infrastructure. We build shared platforms and abstractions that enable product teams to independently develop, evaluate, and launch new search-powered experiences. These platforms provide the guardrails, testing capabilities, observability, and rollout controls needed to prevent reliability, scalability, quality, and latency regressions while supporting rapid product iteration. The team partners closely with: Post-Training on model launches, experimentation, and prompt optimization Search product verticals on new user experiences Inference on GPU efficiencies Indexing and Retrieval on the systems that identify and deliver relevant information Capacity/Fleet team to ensure optimal regionalized provisioning of GPUs and CPUs About the Role We are looking for an Engineering Manager to lead the team responsible for ChatGPT’s Search Product Infrastructure. You will set the technical and organizational direction for the systems that bring search capabilities into ChatGPT. You will guide architectural decisions across search orchestration, model and prompt integration, serving infrastructure, experimentation, observability, evaluation, and product integrations. You will balance immediate launch and product needs with the long-term reliability, scalability, latency, and maintainability of the platform. A central responsibility of this role is creating leverage for Search product verticals. You will lead the development of extensible platforms that allow those teams to independently build, test, and launch features without requiring ongoing invol

About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. Build systems that reduce unnecessary CI work through affected-target detection, dependency graph analysis, test selection, caching, batching, and smarter scheduling. Improve local development workflows so engineers can reproduce CI behavior, debug build failures, and iterate quickly without learning every detail of the build stack. Operate and optimize build infrastructure across Docker/OCI images, Kubernetes-based runners, cloud resources, and remote cache/exec

Overview The Associate Director of Service Engineering leads the reliability, availability, and operational excellence of Natera’s lab-facing platforms. This role ensures that clinical systems, laboratory equipment workflows, and data pipelines operate with high reliability, scalability, and compliance in a regulated healthcare environment. You will lead a team responsible for production stability, incident response, and service health, partnering closely with Production Engineering, Lab Operations, Bioinformatics, Infrastructure, Facilities, and Compliance to support mission-critical genetic testing and diagnostics. Key Responsibilities Leadership & Team Development Lead, mentor, and scale a team of Service Engineers / SREs supporting clinical production systems Establish clear expectations around ownership, on-call readiness, and operational excellence Drive hiring, onboarding, performance management, and career growth Foster a blameless, learning-oriented culture focused on patient impact and reliability Service Reliability & Production Operations Own reliability and availability for production services supporting laboratory operations, reporting, and customer delivery Define and manage SLAs, SLOs, and operational KPIs aligned with clinical and business priorities Lead major incident response, ensuring rapid triage, clear communication, and thorough post-incident reviews Oversee on-call rotations, escalation paths, and operational playbooks Ensure operational readiness and go-live support for new assays, pipelines, and platform capabilities Technical Strategy & Execution Partner with Engineering and Development teams to design resilient, fault-tolerant systems Drive best practices for monitoring, alerting, logging, and observability across lab and cloud platforms Reduce operational toil through automation, tooling, and process improvements Advocate for reliability, performance, and scalability requirements early in t