Design Engineers in United States

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

About the Team We’re hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI’s training and inference frameworks and helps execute frontier experiments. About the Role We’re looking for someone who cares about the developer experience of working in and around OpenAI’s core training and inference frameworks. In this role you will: Be responsible for optimizing the development workflows of the engineers around you Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience Optimize iteration speed, both broadly, and in particular by optimizing specific teams’ CI Improve reliability, for instance, by driving testing strategy for particular components Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to not happen again. Your second instinct is clicking merge on the PR you’ve already written to make it so. You are pragmatic. You have the ability to see the world through a perfectionist’s eyes, but are not yourself a perfectionist. You know which problems to pick and when to switch to making progress on a different problem. You like going end-to-end on things. You love co-design — that feeling when you were only able to find the right solution because you both deeply understand the users that interact with a system and the

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

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Cohere is in a unique and exciting position to grow our go-to-market teams globally! We are expanding our Talent Team and are looking for a dedicated Early Careers & Interns Specialist to help us build a world-class pipeline of future AI talent. In this role, you will design and execute comprehensive early careers programs that attract, develop, and retain top student and recent graduate talent, positioning Cohere as the premier destination for ambitious early-career professionals in AI. As an Early Careers & Interns Specialist, you will: Design and implement strategic early talent programs with clear goals for intern and graduate pipelines Align with early careers frameworks with Cohere's global growth plans and talent needs Story tell the comprehensive learning objectives and core projects for each intern cohort Build and maintain partnerships with top universities and colleges to source high-potential candidates Develop targeted employer branding strategies specifically for student markets Represent Cohere at career fairs and host on-campus recruitment events Partner with the People team to execute seam

Senior Visual Designer Description - HP is seeking an exceptional Senior Visual Designer to elevate the visual experience across consumer printing products and services used by millions of customers worldwide. This role will define and deliver visual design across HP’s ecosystem, combining design excellence, strategic thinking, technical expertise, and user insight to create innovative, user-centered solutions while mentoring designers and strengthening collaboration. As a senior member of the design organization, you will apply visual design expertise, systems thinking, and customer empathy to create intuitive, engaging, and differentiated experiences that strengthen HP’s brand and support measurable business outcomes. You will work closely with cross-functional partners to help shape the next generation of connected print experiences. Core Responsibilities Visual Experience Design Create high-fidelity user interface designs for across web, mobile, and printer front-panel platforms. Develop visual concepts, layouts, illustrations, iconography, motion graphics, and interaction patterns that elevate the customer experience. Customer-Centered Design Collaborate with User Experience designers, marketing, program managers, and engineers to deliver world-class product experiences. Coordinate with development teams to ensure feasible, well-implemented design solutions. Deliver wireframes, prototypes, specifications, style guides, and other high-quality visual assets. Design Systems & Brand Excellence Contribute to HP's design systems, visual standards, and component libraries. Ensure consisten

NVIDIA is seeking an a PCB Library Engineer to join our PCB Design Infrastructure team. In this role, you will help develop and maintain the PCB library assets used across NVIDIA's Data Center, AI, Networking, Automotive, and Graphics products. Working alongside experienced PCB designers, library engineers, mechanical engineers, manufacturing engineers, and component engineers, you will create and validate component footprints, schematic symbols, mechanical components, panel definitions, and other critical design assets that enable successful product development. This position provides an excellent opportunity to build expertise in PCB design, manufacturing, component engineering, and design automation while supporting some of the most advanced computing platforms in the world. What you'll be doing: Develop PCB footprints, padstacks, schematic symbols, and mechanical library content using Cadence PCB design tools. Review component datasheets, package drawings, and engineering specifications to create accurate design libraries. Support library verification, release, and documentation processes. Partner with PCB design, mechanical engineering, manufacturing engineering, and operations teams to resolve library-related issues. Learn and apply industry standards, including IPC requirements, DFM, DFA, and DFT principles. Support quality initiatives to ensure library content is accurate, manufacturable, and scalable. Participate in continuous improvement and automation efforts within the library environment. Develop a strong understanding of PCB fabrication, assembly, and component technologies. What We Need to See: BS degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, Manufacturing Engineering, or a related field or equivalent experience. <p

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 This role is an exciting opportunity to be instrumental in creating magical collaboration workflows within ClickUp. Your focus will be on enabling teams and organizations to work together more effectively, fostering clear communication, coordination, and improved productivity. In this role, you'll have the opportunity to shape the collaboration experience in our products. Responsibilities: Uses AI to gather customer research, generate surveys and tests, and turn insight into clear UX. Prototypes flows, interactions, and logic using Claude Code, Cursor, for rapid iteration with customers and internal stakeholder alignment. Creates high-fidelity UI prototypes that push aesthetics, animation, and visual quality beyond what manual craft alone allows. Automates handoffs to engineering via Figma or vibecoded prototypes built with Claude Code or Cursor. Conduct user research to gain deep insights into user behaviors, pain points, and needs in the collaboration space. Collaborate with cross-functional teams, including product managers, engineers, and researchers, to define product strategy and roadmap for the collaboration experience. Create wireframes, prototypes, and high-fidelity designs that effectively communicate design concepts and interaction models. Conduct usability testing and gather feedback from users to iterate and improve designs. Work closely with front-end developers to ensure the design vision is implemented to the highest standard. Requirements: Minimum of 7 years of experience in product design, with a focus on collaboration or communication products. Strong portfolio demonstrating a track

Datadog’s Technical Solutions organization includes 1,200+ sales engineers, support engineers, post-sales experts, and solution architects. They run on an ecosystem of enterprise platforms and internal tools that directly shape how we serve customers. Technical Solutions Operations (“TSO”) owns that ecosystem. We manage the full lifecycle of the systems TS depends on: Zendesk, Jira, Confluence, and a growing portfolio of off-the-shelf and purpose-built tools. We do the work to operate, maintain, and evolve the platforms powering daily workflows across TS. When a vendor tool reaches its limits, we extend it through customization, integration, or targeted solution development, tapping internal partners across Datadog as needed. We’re looking for a Systems Engineer who wants to own enterprise platforms end-to-end. You go from understanding the business process, to designing the right solution (whether that’s configuration, integration, or code), to measuring whether it actually moved the needle. 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: Own enterprise systems through their full lifecycle. You’ll be the technical owner for one or more platforms that TS relies on daily. That means understanding how the system is used, where it’s falling short, what’s coming from the vendor roadmap, and what needs to change. You drive improvements from assessment through implementation. Engineer solutions that create leverage. Not every problem is solved by configuration. You’ll build and evolve enterprise systems, integrations, automations, and internal tools that multiply the effectiveness of 1,200+ technical experts. Where AI can make a solution smarter (e.g., intelligent routing, automated triage, agent-assisted workflows), you'll include AI in the initial design, no

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors, software, and data center systems that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our U.S. engineering teams contribute to the hardware and software platforms that support the next generation of AI systems. The Opportunity We are looking for a computer engineering, electrical engineering, or computer science student or recent graduate to join the BMC Development team as a Firmware Engineering Intern. You will work with experienced engineers on low-level and embedded firmware that supports the operation, control, and manageability of advanced compute systems. This internship provides hands-on experience in firmware development, test automation, engineering experiments, and lab-based system testing in a Linux development environment. You will own clearly defined technical tasks with guidance from the team and contribute to production-quality engineering work. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You Will Do Contribute to the design, implementation, and testing of system and embedded firmware. Develop and maintain firmware and supporting software in C, C++, or Python. Support firmware development and debugging in a Linux-based engineering environment. Create automated tests and scripts that improve firmware validation, test coverage, and engineering efficiency. Contribute to continuous integration and delivery workflows for firmware development and testing. Plan and conduct well-defined engineering experiments, record results accurately, and draw conclusions from test data. Support lab setup, system configuration, hardware bring-up, and firmware testing. Use debugging and diagnostic techn

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors, software, and data center systems that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our U.S. engineering teams contribute to the hardware and software platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the BMC Engineering team as a Graduate Firmware Engineer. You will develop low-level and embedded firmware that supports the operation, control, monitoring, and validation of advanced compute systems. You will work with experienced firmware, hardware, systems, and software engineers throughout the development lifecycle. The role combines hands-on implementation with automated testing, lab-based debugging, hardware bring-up, and analysis of interactions between firmware and the underlying platform. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Design, implement, test, and maintain system and embedded firmware in C, C++, or Python. Take ownership of defined firmware features and deliver them from requirements and design through implementation, validation, and documentation. Develop and debug firmware in a Linux-based engineering environment using appropriate diagnostic tools and techniques. Create automated tests and scripts that improve firmware validation, test coverage, and engineering efficiency. Contribute to continuous integration and delivery workflows for firmware development and testing. Plan and conduct engineering experiments, analyze test data, and communicate findings clearly. Support lab setup, system configuration, hardware bring-up, and firmware validation on development platforms. Investigate firmware behavior and hardware-software

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity As a Systems Engineering Intern, you will contribute to projects that combine hardware, firmware, and software engineering for advanced AI compute platforms. You will work with experienced engineers on subsystem design, laboratory testing, system validation, automation, and performance analysis. The internship provides hands-on experience with modern hardware development and system-level engineering. You will own clearly defined technical tasks with guidance from the team and document your methods, results, and conclusions. What You Will Do Support the design and testing of CPU and high-speed input and output subsystems for advanced compute platforms. Run laboratory tests and measurements to help evaluate performance, power, signal behavior, and reliability. Contribute to system-level validation by creating scripts and tools that streamline testing, data collection, and analysis. Explore emerging input and output technologies, including PCIe 6.0 and 800G Ethernet, and learn how they support advanced computing workloads. Assist with investigations into platform power, cooling, and energy efficiency, including liquid-cooling systems for high-performance processors. Use power meters, oscilloscopes, logic analyzers, or comparable lab equipment under appropriate supervision. Analyze test results, identify unexpected behavior, and work with engineers to reproduce and investigate issues. Collaborate across hardware, firmware, software, m