Cpu Floorplan Lead in India

Silicon Verification Engineer Multiple roles across different levels 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. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. The verification team sits within the Silicon design team and is responsible for ensuring that the RTL created by the logical design team and used by the physical design team matches the architecture specification for Graphcore silicon. The silicon verification engineer is responsible for verification activities within Graphcore, helping the team meet the company objectives for quality silicon delivery. Responsibilities Verification planning, specification and closure of functional coverage Providing feedback to architects Test generation and failure diagnosis/triage Contributing to shared verification infrastructure Ensuring good communication between sites Essential skills: • Verification experience in relevant industry • Proven leadership and planning skills • Highly motivated, a self starter, and a team player • Ability to work across teams and programming languages to find root causes of deep and complex issues • Experience of the verification process applied in CPU and/or ASIC environments • System Verilog, Python, C++, Linux Desirable skills: • UVM • SVA • Assembly languages • LLVM, GCC • DVCS e.g. Git • SGE or other DRMS • XML and XPath/XSLT • Web programming – HTML/DOM, Javascript, SQL Benefits: In addition to a competitive salary, Graphcore offers a competitive benefit

Silicon Verification Engineer Multiple roles across different levels 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. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. The verification team sits within the Silicon design team and is responsible for ensuring that the RTL created by the logical design team and used by the physical design team matches the architecture specification for Graphcore silicon. The silicon verification engineer is responsible for verification activities within Graphcore, helping the team meet the company objectives for quality silicon delivery. Responsibilities Verification planning, specification and closure of functional coverage Providing feedback to architects Test generation and failure diagnosis/triage Contributing to shared verification infrastructure Ensuring good communication between sites Essential skills: • Verification experience in relevant industry • Proven leadership and planning skills • Highly motivated, a self starter, and a team player • Ability to work across teams and programming languages to find root causes of deep and complex issues • Experience of the verification process applied in CPU and/or ASIC environments • System Verilog, Python, C++, Linux Desirable skills: • UVM • SVA • Assembly languages • LLVM, GCC • DVCS e.g. Git • SGE or other DRMS • XML and XPath/XSLT • Web programming – HTML/DOM, Javascript, SQL Benefits: In addition to a competitive salary, Graphcore offers a competitive benefit

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU/storage, GPU, and network lifecycle management to drive efficiency, accountability and support dynamic optimization of our resources. Implement fault-tolerant and resilient

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’s cloud spend is in billions of dollars per year. Hence, it is critical for us to govern and optimize our cloud spend, both for margins and long-term competitive advantage. Cloud Efficiency team’s charter is to build scalable products that enable governance, monitoring and optimization of cloud spend. Think of this as Observability for cloud costs and efficiency. The team’s vision is to “Transform cloud spend into a competitive advantage by empowering teams to continuously optimize the per-unit cost.” In order to improve the overall cloud efficiency (i.e. cost per unit), it is critical to build monitoring products that collate costs with other factors such as utilization, attribution, hardware performance and architecture. Hence, there is an opportunity to build a unified, self-serve cloud efficiency product across Snowflake, that delivers actionable, real-time efficiency datasets through streamlined user experiences. This will enable thousands of engineers at Snowflake and will elevate cloud efficiency at Snowflake for long-term success. When developing these solutions, we think about the problem end-to-end: how do we collect data from different stacks (e.g. costs from AWS, GCP, Azure and CPU, Memory, Utilization) across Snowflake reliably, how do we store it eff