About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver 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 some of the world's most transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the future of AI computing. The Opportunity As Technical Services Director, you will lead the teams that operate and evolve Graphcore's engineering labs, high-performance computing (HPC) platforms, and data center environments globally. You will be accountable for reliable, secure, cost-effective infrastructure that supports demanding engineering, AI, silicon-development, and validation workloads. This role combines people leadership, infrastructure strategy, operational excellence, capacity and financial planning, procurement, and program delivery. You will partner with Engineering, Information Technology, Security, Finance, Facilities, Supply Chain, customers, and external suppliers. The position is based onsite in Austin and requires travel to company facilities, data centers, and supplier locations, including international travel. What You'll Do Lead, recruit, mentor, and develop the systems administration, lab operations, and technical services teams responsible for the facility supporting global Engineering and Research and Development. Own the reliability, efficiency, protection, safety, supportability, and continuous improvement of engineering labs, HPC systems, and infrastructure facilities. Establish service levels, operating standards, escalation paths, performance measures, monitoring, observability, automation, ticketing, and configuration-management practices. Translate engineering and customer requirements into infrastructure roadmaps, capacity p
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About Us Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. 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. Job Summary Working within the logical design team, the silicon logical design engineer is responsible for a wide range of logical design tasks. The team is responsible for delivering the Microarchitecture and RTL design to implement the chip architecture specification for Graphcore Silicon, working closely with other engineers within the Silicon team. The successful candidate will be responsible for helping the team deliver high quality micro-architecture and RTL for Graphcore chips, working within the logical design team and with the broader Silicon team to ensure we meet the company objectives for Silicon delivery. Responsibilities and Duties Integrate IP and subsystems into top-level SoC designs Develop and maintain build and configuration environments Perform synthesis, linting, CDC/RDC, and timing checks at the SoC level Support verification and physical design teams through clean interface hand-offs Debug and resolve integration-related issues across multiple hierarchies Contribute to the continuous improvement of integration flows and automation Producing high quality microarchitecture and other documentation Ensure good communication between sites to maintain consistent working practises Candidate Profile Essential skills: Logical design experience in relevant industry Experience range 8-12 years in Semiconductor Industry/Product development exposure. Be highly motivated, a self-starter, and a team player Ability to work across teams and debugging issues seen to find root cau
About Us Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. 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. Job Summary Working within the logical design team, the silicon logical design engineer is responsible for a wide range of logical design tasks. The team is responsible for delivering the Microarchitecture and RTL design to implement the chip architecture specification for Graphcore Silicon, working closely with other engineers within the Silicon team. The successful candidate will be responsible for helping the team deliver high quality micro-architecture and RTL for Graphcore chips, working within the logical design team and with the broader Silicon team to ensure we meet the company objectives for Silicon delivery. Responsibilities and Duties Integrate IP and subsystems into top-level SoC designs Develop and maintain build and configuration environments Perform synthesis, linting, CDC/RDC, and timing checks at the SoC level Support verification and physical design teams through clean interface hand-offs Debug and resolve integration-related issues across multiple hierarchies Contribute to the continuous improvement of integration flows and automation Producing high quality microarchitecture and other documentation Ensure good communication between sites to maintain consistent working practises Candidate Profile Essential skills: Logical design experience in relevant industry Experience range 4-8 years in Semiconductor Industry/Product development exposure. Be highly motivated, a self-starter, and a team player Ability to work across teams and debugging issues seen to find root caus
Sigmoid empowers enterprises to make smarter, data-driven decisions by blending advanced data engineering with AI consulting. We collaborate with some of the world’s leading data-rich organizations across sectors such as CPG-retail, BFSI, life sciences, manufacturing, and more to solve complex business challenges. Our global team specializes in cloud data modernization, predictive analytics, generative AI, and DataOps, supported by 10+ delivery centers and innovation hubs, including a major global presence in Bengaluru and operations across the USA, Canada, UK, Netherlands, Poland, Singapore, and India. Recognized as a leader in the data and analytics space, Sigmoid is backed by Peak XV Partners and has consistently received accolades for innovation and rapid growth. Highlights include being named a ‘Leader’ in ISG’s Specialty Analytics Services for Supply Chain (2024), a two-time ‘India Future Unicorn’ by Hurun India, and a four-time honoree on both the Inc. 500 and Deloitte Technology Fast 500 lists. Technical Lead – Data Engineering As a Technical Lead, you will be responsible in building a highly-scalable and extensible big data platform that provides the foundation for collecting, storing, modeling, and analyzing massive data sets from multiple channels. This position reports to Engineering Manager. Responsibilities: Align Sigmoid with key Client initiatives Interface daily with customers across leading Fortune 500 companies to understand strategic requirements Connect with VP and Director level clients on a regular basis. Travel to client locations Ability to understand business requirements and tie them to technology solutions Facilitate in Technical Aspects Design, develop and evolve highly scalable and fault-tolerant distributed components using Big data technologies. Excellent experience in Application development and support, integration development and data management. Provide technical leadership and manage it day to day basis Guiding developers
Sigmoid empowers enterprises to make smarter, data-driven decisions by blending advanced data engineering with AI consulting. We collaborate with some of the world’s leading data-rich organizations across sectors such as CPG-retail, BFSI, life sciences, manufacturing, and more to solve complex business challenges. Our global team specializes in cloud data modernization, predictive analytics, generative AI, and DataOps, supported by 10+ delivery centers and innovation hubs, including a major global presence in Bengaluru and operations across the USA, Canada, UK, Netherlands, Poland, Singapore, and India. Recognized as a leader in the data and analytics space, Sigmoid is backed by Peak XV Partners and has consistently received accolades for innovation and rapid growth. Highlights include being named a ‘Leader’ in ISG’s Specialty Analytics Services for Supply Chain (2024), a two-time ‘India Future Unicorn’ by Hurun India, and a four-time honoree on both the Inc. 500 and Deloitte Technology Fast 500 lists. Technical Lead – Data Engineering As a Technical Lead, you will be responsible in building a highly-scalable and extensible big data platform that provides the foundation for collecting, storing, modeling, and analyzing massive data sets from multiple channels. This position reports to Engineering Manager. Responsibilities: Align Sigmoid with key Client initiatives Interface daily with customers across leading Fortune 500 companies to understand strategic requirements Connect with VP and Director level clients on a regular basis. Travel to client locations Ability to understand business requirements and tie them to technology solutions Facilitate in Technical Aspects Design, develop and evolve highly scalable and fault-tolerant distributed components using Big data technologies. Excellent experience in Application development and support, integration development and data management. Provide technical leadership and manage it day to day basis Guiding developers
About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary environment. 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: Lead mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We're seeking a Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate the software used to manufacture, qualify, and deliver our hardware from the factory. You will work across the stack to create the infrastructure that runs internally and externally to coordinate all aspects of the production process. You will create the critical tools and procedures to execute, capture, process, and present the data resulting from the end to end assembly and validation of our hardware across multiple vendors and sites. This role is hands-on and high-ownership. You will work closely across teams both internal and external to define the standards that will be used across our products to ensure the velocity and quality of our 1P hardware. You will own the implementation, deployment, and output of these systems as well their continued maintenance and SLAs. Location: San Francisco, CA (Hybrid: 3 days/week onsite). Relocation assistance available. In this role, you will: Design, develop, and maintain the software infrastructure for manufacturing process execution and data export. Own integration across internal customers and vendor systems and processes. Build and maintain the CI, release, and delivery pipeline of tooling to external partners. Build and maintain internal systems to ingest, process, deliver, and visualize critical data for internal teams and systems. Build system health monitoring, telemetry, remote d
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking a highly skilled Physical Design Engineer with deep expertise in physical design and methodology. This individual contributor role sits within our physical design team and is central to delivering power, performance, and area (PPA) optimized datapath and interconnect solutions for next-generation AI accelerators. You’ll work closely with RTL designers to define and execute on physical design strategies. You will develop tools, flows and methodologies to increase team productivity. Your work will directly impact silicon’s performance and cost efficiency, as well as the team’s execution velocity and quality. In this role, you will: Develop, build and own tools, flows and methodologies for physical implementation Own physical implementation of floorplan blocks from floorplanning to final signoff Collaborate with RTL designers to drive optimal block implementation solutions Analyze and optimize design for timing, power, and area trade-offs, working in collaboration with EDA vendors and ASIC partners Qualifications: BS w/ 4+ or MS with 2+ years or PhD with 0-1 year(s) of relevant industry experience in physical design and methodology development Demonstrated success in taping out complex silicon designs Hands-on experience with block physical implementation and PPA convergence Strong coding experience with python, bazel, TCL Strong experience building physical design tools, flows and methodologies Strong understanding of microarchitecture, RTL design,
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing & quality engineer, who will be responsible for driving technical initiatives related to the manufacturing, quality and reliability of our AI supercomputer hardware systems to ensure product success from concept to launch and through mass production. You’ll have the opportunity to coordinate with functional SMEs and work with a wide range of stakeholders, from design engineering and operations teams, TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. 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: Own the integrated manufacturing and quality readiness for a product across L6, L10, and L11, with clear gates, milestones, deliverables, owners, and closure criteria. Lead readiness of process flows, tooling, fixtures, assembly operations, test interfaces, and production controls. Review and contribute to work instructions. Translate product requirements into qualification plans, process controls, test requirements and acceptance criteria with design engineering and Area SMEs Coordinate and drive execution of product and process qualification, reliability testing, and validation with the relevant SMEs. Maintain traceable evidence that assigned products and processes meet agreed performance, reliability,
About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro
About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with
About the Team OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions. Our work sits at the intersection of technical strategy, product development, engineering, and deployment. We partner closely with customers and internal engineering teams to solve complex infrastructure challenges spanning compute, power, cooling, controls, and facility efficiency. About the Role We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments. This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment. The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries. Key Responsibilities Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure. Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios. Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize
"The job purpose of a Cluster Manager - Diffusion in cell process within solar manufacturing is to accelerate the adoption and integration of advanced cell processing technologies among solar companies. This role involves strategizing, coordinating collaborations, managing resources efficiently, and advocating for policies that support innovation and industry growth. The goal is to enhance operational efficiency, competitiveness, and sustainability within the solar manufacturing sector. Design DOEs for emitter layer, Junction performance enhancement, ECV profiling. Circulate within team and complete tast within speacific time interval Source: Adani Group | Job ID: 57353
About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. In this role you will: As a Hardware Test Engineer, you will work on Machine Learning/AI hardware system projects to craft the solutions for current and future data center deployments. You will bring a strong understanding of hardware system testing, excellent project management skills, and the ability to collaborate across multiple teams to ensure efficient lab operations. You will be responsible for designing, implementing, and executing comprehensive test plans that ensure the reliability, performance, and scalability of our supercomputing hardware systems. You will develop detailed test plans and methodologies tailored to hardware components, including processors, memory modules, custom accelerators and interconnects. You will collaborate with hardware design, manufacturing, firmware teams and vendors to identify, analyze, and resolve issues affecting hardware, power, thermal and high-speed interconnects. You will perform in-depth debugging on the hardware system Excellent analytical skills to diagnose hardware issues, troubleshoot problems, and propose solutions. Ability to interpret complex test data, identify trends, and draw meaningful conclusions. High-speed links, with a focus on SerDes (Serializer/Deserializer) technology to assess signal integrity, error rates, and overall link performance. You will collaborate with the lab manager to maintain the equipment and hardware systems, including oscilloscopes, thermal test chambers, liquid cooling systems, and other mea
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit
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