High Performance Workstation Business Development Manager Amd in United States

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking an exceptional Senior-level Physical Design Engineer to drive top-level implementation of our complex AI and CPU System-on-Chip designs. You'll orchestrate cross-disciplinary collaboration, implementing sophisticated floorplans, power grids, and clock networks while ensuring design closure at the chip level. If you excel at managing the complexity of full-chip physical design and want to deliver next-generation AI hardware, we need your expertise. This role is hybrid , based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A seasoned physical design engineer who thrives on complex, full-chip implementation challenges. Expert at collaborating across disciplines, working effectively with architecture, RTL, and packaging teams. Passionate about optimizing chip-level implementations for power, performance, and area. Detail-oriented professional who drives design closure while maintaining quality and meeting aggressive schedules. What We Need 8+ years of top-level SOC physical design experience on complex, multi-million gate designs. Deep expertise in hierarchic

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Field Sales Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is remote based out of North America with preference near one of our main hubs Santa Clara, CA; Boston, MA; or Toronto,ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.” You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life. You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon. Work directly with customers in pre-sales

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking an experienced Project Manager to lead our ERP implementation and drive delivery across technical and business teams. In this role, you will bridge Solution Architects with stakeholders across Sales, Supply Chain, Finance, Trade, Infosec, and Engineering to keep the program aligned, accountable, and moving forward. This role is hybrid, based out of Santa Clara, CA, or Austin, TX. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are An experienced project manager who has led complex ERP implementations, such as NetSuite or SAP. Skilled in project management methodologies and tools, including Jira and Asana. A strong interpersonal communicator who can influence, align, and mediate across technical and business teams. Able to synthesize complex technical discussions into clear, actionable reporting for varied stakeholders. What We Need Define project scope, milestones, deliverables, and governance for the ERP implementation. Manage external consultants, monitor adherence to statements of work, and drive accountability for delivery. Coordinate Sales, Supply Chain, Finance, Trade, Infosec, Engineering, Solution Architecture, and o

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a highly skilled and experienced Engineer to lead post-silicon power characterization and correlation activities for cutting-edge semiconductor products. In this role, you will be responsible for developing and executing detailed power measurement strategies on silicon, correlating results with pre-silicon models, and driving improvements across power architecture, design, and modeling methodologies. You will serve as a key technical leader, interfacing across design, architecture, validation, and systems teams to ensure silicon meets power and performance specifications under all operating conditions. This role is hybrid, based out of Toronto, ON or Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who you are A Principal-level engineer with 8+ years in silicon power analysis and characterization, and a Master’s or PhD in EE, CE, or related field. Deep understanding of digital and mixed-signal power domains, including DVFS, leakage vs. dynamic power, and power gating. Highly proficient in lab-based power measurement using oscilloscopes, current probes, power analyzers, and SMUs, plus Python/Perl/MATLAB

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Our IP delivery timelines are set as much by flow maturity as by design work. This role develops, deploys, and owns the RTL-to-GDSII methodology the IP physical design team runs on, so a new block, node, or customer variant starts from a working flow instead of a cold start. This role is hybrid, based out of Toronto, ON; Austin, TX, or Belgrade, Serbia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A physical design or CAD methodology engineer who has built flows that production teams depend on daily. Automation-minded, happiest when you are removing manual steps and making PPA exploration repeatable. Building with AI as part of how you develop flows, and opinionated about where LLMs and ML-driven optimization genuinely help versus where they do not. An effective partner to design teams and EDA vendors, and a clear writer who documents flows well enough that others can run them without you. What We Need An Engineer with 5+ years developing and supporting physical design methodology or CAD flows in production use. Expertise with industry-standard tools (FusionCompiler/ICC2, Innovus/Genus, PrimeTime, RedHawk) and scripting languages (T

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a SoC Physical Design Verification Engineer to drive full-chip signoff and ensure manufacturable, high-quality silicon across advanced technology nodes. You’ll lead physical verification closure (DRC, LVS, ERC, etc.), debug issues using standard industry PV tools, and collaborate across RTL, PD, CAD, and packaging teams to achieve successful tapeouts. If you thrive in a fast-paced environment and enjoy solving complex challenges in cutting-edge silicon, we’d love to hear from you. This role is hybrid , based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A seasoned engineer with a strong background in CPU/IP/SoC physical verification and tapeout closure. A hands-on problem solver who excels at debugging and driving signoff through complex verification flows. A collaborative team player who works effectively across RTL, PD, CAD, and foundry interfaces. A mentor and technical leader passionate about building efficient, manufacturable silicon. What We Need BS/MS in Electrical/Electronics Engineering (or related) with 7–14 years of hands-on CPU/IP/SoC physical verif

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. This role sits at the center of cutting-edge AI hardware development, keeping the servers, PCIe systems, and engineering infrastructure running that power next-generation compute. You’ll be hands-on with rapidly evolving prototype and production systems, installing, maintaining, and troubleshooting hardware in fast-paced R&D and data center environments. Acting as a critical bridge between hardware engineers, software teams, and IT, you’ll help ensure seamless access to the platforms that turn ideas into working silicon and systems. This role is onsite, based out of Toronto, Canada or Austin, Texas. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on hardware professional who enjoys building, maintaining, and troubleshooting complex computing systems. Comfortable working in fast-paced R&D environments where hardware, firmware, and software are constantly evolving. Knowledgeable in computer architecture, operating systems, and hardware diagnostics, with strong problem-solving skills. Collaborative, detail-oriented, and motivated to improve processes through documentation, scripting, and automation. What We Need Inst

Principal Embedded SW/FW Engineer (Bringup) - Austin, Tx, USA Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential: Understanding of ML

About us 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 Reporting to the Quality leadership within Manufacturing Operations, the Senior Reliability Scientist is responsible for leading reliability activities across complex, high-performance systems. Working closely with established reliability experts and cross-functional teams, this role uses experimental data and advanced modelling to inform design decisions, validate product reliability and optimise serviceability strategies, including spares provisioning. The Team The Quality team within Manufacturing Operations is responsible for ensuring product robustness, reliability and lifecycle performance across Graphcore’s hardware portfolio. The team includes experienced reliability specialists and works closely with technology research, chip, board, system design, platform and operations teams to translate reliability insights into actionable improvements across the product lifecycle. Responsibilities and Duties: · Define and refine reliability requirements across silicon, board and system levels, working in partnership with research and design teams · Apply ad

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for talented systems developers and researchers to join the Snowflake AI Research team and advance the state of the art in LLM inference systems and optimization . Our mission is to build the next generation of high-performance and intelligent inference systems . We optimize not only how fast and efficiently models run, but also how quickly inference systems can adapt to new models, architectures, hardware, and workloads. Our work spans the full inference stack—from distributed serving and runtime systems to GPU kernels and model-system co-design. We explore techniques such as adaptive parallelism, speculative and parallel decoding, disaggregated inference, scheduling and batching, KV-cache optimization, model swapping, quantization, and GPU kernel optimization to push the frontier of latency, throughput, scalability, and cost. Beyond optimizing individual models, we are building intelligent and adaptive inference systems that can automate performance optimization—rapidly profiling new models and workloads, identifying bottlenecks, selecting effective execution strategies, and adapting system configurations with minimal manual tuning. We embrace AI-native engineering , using AI not only as the workload we optimize, but also as a tool to accelerate system deve

About the Team The Core Services organization builds and runs the mission-critical online services that product teams rely on in production. We own foundational distributed systems and platform capabilities that enable reliable execution, high-performance services, and large-scale file/data needs across our products. This team is distinct from developer infrastructure and data infrastructure—our focus is production service foundations and core runtime services. About the Role We’re hiring an Engineering Manager, Core Services to help lead teams responsible for highly reliable, high-scale distributed systems that sit on the critical path for OpenAI products. Your team will own foundational production systems that OpenAI’s product engineering teams build on. You’ll collaborate closely with product and infrastructure partners to ship reliable services quickly, and help scale systems and teams as OpenAI grows. You’ll partner closely with senior engineering leaders to scale the org, mature operations, and drive major platform initiatives. This role requires strong technical ability. You’ll be responsible for: Managing and growing a high-performing team of infrastructure engineers. Leading teams building and operating large, critical production platforms, including cluster reliability, scaling, and rollout safety. Building and operating mission-critical distributed systems with strong operational rigor (SLOs, incident response, capacity planning, reliability). Setting technical direction for platform foundations such as workflow/orchestration capabilities, large-scale file/blob/storage services, and core service foundations. Partnering with a broad set of stakeholders, including product engineering, adjacent infrastructure teams, and (where relevant) finance/cost partners. Coaching, mentoring, and developing engineers and emerging leaders. You might thrive in this role if you: Have significant experience leading teams that run mission-critical infrastructure in production

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As Manager (Player & Coach) of the Solution Architect team, you will lead and mentor a team of Solution Architects who will partner closely with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide repeatable deployments and proofs of value for customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of owning discovery calls, demos, technical scoping and driving POC’s through to execution as well as designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership Lead, mentor, and grow a team of Solution Architects, providing guidance on technical direction, project execution, and professional development. Set clear goals and ensure timely, high-quality d

The Manager of Networking at Datadog leads the global management of network services across all Datadog offices worldwide. This role is responsible for ensuring seamless, high-performance Wi-Fi and direct internet access in our global offices and conference room technology, supporting a rapidly growing global enterprise. As Datadog continues to grow rapidly, this role plays a critical part in scaling both the team and network infrastructure to meet increasing demand. This is a hybrid role that sits in global headquarters in New York city and requires three days in the office each week with occasional travel to our offices around the world. What You’ll Do: Lead the global network engineering teams, managing both full-time employees and third-party vendors to ensure consistent and high-quality service delivery for Datadog offices worldwide. Oversee the design, deployment and scaling of office network infrastructure, including Wi-Fi (Cisco Meraki) and edge networking devices (Cisco, Palo Alto, Juniper, and others), ensuring these services operate according to Datadog's defined service level objectives. Define and implement standards, policies, and processes for network infrastructure to ensure security, reliability and scalability. Collaborate with IT Security, Enterprise Technology, and Workplace teams to align network services with broader IT and business objectives. Develop and track operational metrics for service availability, network performance, driving continuous improvement and optimization. Who You Are: An experienced people manager with at least 5+ years of leadership experience managing teams of network engineers. Proven expertise in Wi-Fi network engineering, including deep knowledge of Cisco Meraki and edge networking solutions from vendors like Cisco, Palo Alto and Juniper. Experience managing large-scale office technology projects in global enterprises with more than 10 offices and 7,000+ employees, ensuring infrastructure keeps pace with ra

About the Team Full Stack engineers within the Fleet Scheduling team are dedicated to building intuitive and scalable interfaces that empower researchers to efficiently manage AI workloads across some of the largest supercomputers in the world. Our focus is on developing robust, high-performance systems that provide real-time insights, resource tracking, and seamless interaction with complex infrastructure. We aim to optimize resource allocation, minimize operational overhead, and create user-friendly tools that enhance researcher productivity and system transparency. About the Role You will design, develop, and operate web-based systems that provide a powerful and intuitive interface to OpenAI’s supercomputing clusters. You will collaborate closely with researcher, product and infrastructure teams to deliver scalable solutions that enable seamless monitoring, job scheduling, and resource management. This is an opportunity to work at the cutting edge of AI infrastructure, designing tools that scale to exascale workloads while maintaining usability and performance. 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 and develop full-stack web applications to track, monitor, and manage large-scale AI workloads in real time. Collaborate with researchers and infrastructure teams to translate complex operational needs into intuitive UIs and scalable backends. Build data visualization tools (e.g., Gantt charts, dashboards) to provide insights into job scheduling and resource allocation. Optimize backend services to handle massive data throughput while ensuring low-latency performance and high availability. Implement frontend components that provide seamless interactions with scheduling, storage, and compute systems. Ensure system security, reliability, and scalability across globally distributed supercomputing infrastructure. You might thrive i

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf