Key Responsibilities Architect and design OpenStack-based private cloud solutions tailored to customer needs. Drive infrastructure design across compute, storage, and network components. Work with cross-functional teams to integrate OpenStack with existing or new platforms. Define and implement best practices for cloud infrastructure, including HA, scalability, and performance tuning. Collaborate with DevOps teams to align infrastructure automation with deployment pipelines. Lead customer engagements and translate business requirements into technical architectures. Ensure compliance, security, and resiliency standards are embedded in all solutions. Key Skills & Experience Minimum 8 years of experience in cloud and infrastructure architecture. Strong experience in OpenStack components : Nova, Neutron, Cinder, Glance, Swift, etc. Deep domain expertise in at least one of the following: Cloud Infrastructure : Compute orchestration, virtualization, HA design. Storage : Block/Object storage solutions (Ceph, Swift, etc.). Networking : SDN, virtual networks, overlay networks, Neutron plugins. Proficient in container technologies and orchestration (Kubernetes is a plus). Experience with tools like Ansible, Terraform, or other automation frameworks. Familiarity with Linux internals, scripting, and system performance monitoring. Strong problem-solving, documentation, and customer-facing skills.
Job Summary We are seeking an experienced GPU Programming Engineer to join our team. In this role, you will focus on developing, optimizing, and deploying GPU-accelerated solutions for high-performance machine learning workloads. The ideal candidate has strong expertise in GPU programming across one or more platforms (e.g., NVIDIA CUDA, AMD ROCm/HIP, or OpenCL) and is comfortable working at the intersection of parallel computing, performance tuning, and ML system integration. Key Responsibilities Develop, optimize, and maintain GPU-accelerated components for machine learning pipelines using frameworks such as CUDA, HIP, or OpenCL Analyze and improve GPU kernel performance through profiling, benchmarking, and resource optimization. Optimize memory access, compute throughput, and kernel execution to improve overall system performance on the target GPUs. Port existing CPU-based implementations to GPU platforms while ensuring correctness and performance scalability. Work closely with system architects, software engineers, and domain experts to integrate GPU-accelerated solutions. Required Qualifications Bachelor's or master's degree in computer science, Electrical Engineering, or a related field. 3+ years of hands-on experience in GPU programming using CUDA, HIP, OpenCL, or other GPU compute APIs. Strong understanding of GPU architecture, memory hierarchy, and parallel programming models. Proficiency in C/C++ and hands-on experience developing on Linux-based systems. Familiarity with profiling and tuning tools such as Nsight, rocprof, or Perfetto. Preferred Qualifications Familiarity with cuDNN, TensorRT, OpenCL, or other GPU computing libraries.
Key Responsibilities: Architect and implement container orchestration solutions using Kubernetes in production-grade environments. Lead the design and integration of OpenStack with Kubernetes-based platforms. Collaborate with infrastructure, DevOps, and software teams to design cloud-native applications and CI/CD pipelines. Define architectural standards, best practices, and governance models for Kubernetes-based workloads. Assess current system architecture and recommend improvements or migrations to Kubernetes. Mentor and guide junior engineers and DevOps teams on Kubernetes and cloud-native tools. Troubleshoot complex infrastructure and containerization issues. Key Requirements: 8+ years of experience in IT architecture with at least 4 + years working on Kubernetes. Deep understanding of Kubernetes architecture (control plane, kubelet, etcd, CNI plugins, etc.) Strong hands-on experience with containerization technologies like Docker and container runtimes. Proven experience working with OpenStack and integrating it with container platforms. Solid knowledge of cloud infrastructure , networking , and persistent storage in Kubernetes. Familiarity with Helm , Istio , service mesh , and other cloud-native tools is a plus. Experience with CI/CD pipelines , infrastructure as code (e.g., Terraform), and GitOps practices. Excellent problem-solving skills and ability to work in fast-paced environments. Preferred Qualifications: Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD) Experience with multiple cloud platforms (AWS, Azure, GCP, or private cloud) Background in networking or storage architecture is highly desirable.
Key Responsibilities : - Architect and implement container orchestration solutions using Kubernetes in production-grade environments. - Lead the design and integration of OpenStack with Kubernetes-based platforms. - Collaborate with infrastructure, DevOps, and software teams to design cloud-native applications and CI/CD pipelines. - Define architectural standards, best practices, and governance models for Kubernetes-based workloads. - Assess current system architecture and recommend improvements or migrations to Kubernetes. - Mentor and guide junior engineers and DevOps teams on Kubernetes and cloud-native tools. - Troubleshoot complex infrastructure and containerization issues. Key Requirements : - 8+ years of experience in IT architecture with at least 4+ years working on Kubernetes. - Deep understanding of Kubernetes architecture (control plane, kubelet, etcd, CNI plugins, etc.) - Strong hands-on experience with containerization technologies like Docker and container runtimes. - Proven experience working with OpenStack and integrating it with container platforms. - Solid knowledge of cloud infrastructure, networking, and persistent storage in Kubernetes. - Familiarity with Helm, Istio, service mesh, and other cloud-native tools is a plus. - Experience with CI/CD pipelines, infrastructure as code (e.g., Terraform), and GitOps practices. - Excellent problem-solving skills and ability to work in fast-paced environments. Preferred Qualifications : - Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD) - Experience with multiple cloud platforms (AWS, Azure, GCP, or private cloud) - Background in networking or storage architecture is highly desirable.
Key Responsibilities - Architect and design OpenStack-based private cloud solutions tailored to customer needs. - Drive infrastructure design across compute, storage, and network components. - Work with cross-functional teams to integrate OpenStack with existing or new platforms. - Define and implement best practices for cloud infrastructure, including HA, scalability, and performance tuning. - Collaborate with DevOps teams to align infrastructure automation with deployment pipelines. - Lead customer engagements and translate business requirements into technical architectures. - Ensure compliance, security, and resiliency standards are embedded in all solutions. Key Skills & Experience - Minimum 8 years of experience in cloud and infrastructure architecture. - Strong experience in OpenStack components: Nova, Neutron, Cinder, Glance, Swift, etc. - Deep domain expertise in at least one of the following: - Cloud Infrastructure: Compute orchestration, virtualization, HA design. - Storage: Block/Object storage solutions (Ceph, Swift, etc.). - Networking: SDN, virtual networks, overlay networks, Neutron plugins. - Proficient in container technologies and orchestration (Kubernetes is a plus). - Experience with tools like Ansible, Terraform, or other automation frameworks. - Familiarity with Linux internals, scripting, and system performance monitoring. - Strong problem-solving, documentation, and customer-facing skills.
4-8 years of hands-on experience in OpenBMC and data-model protocols between BMC services, e.g. MCTP, PLDM/PSDM, CXL, RedFish, RAS API Attends and is familiar with Open Compute Global Summit and its workgroups. Expert understanding of interfacing application layer, Kernel Layer and Hardware in OpenBMC SW architecture. Experience in Linux device drivers is an added advantage. Experience in controlling / retrieving from the datacenter servers from BMC. Expert level debugging throughout the workflow. Candidates should interface with customer for requirement gathering / analysis to derive the efforts, timeline and identify the risks, dependency and mitigate the challenges. While contributing individually, guide the team technically and move towards the right directions.
Key Responsibilities Architect and design OpenStack-based private cloud solutions tailored to customer needs. Drive infrastructure design across compute, storage, and network components. Work with cross-functional teams to integrate OpenStack with existing or new platforms. Define and implement best practices for cloud infrastructure, including HA, scalability, and performance tuning. Collaborate with DevOps teams to align infrastructure automation with deployment pipelines. Lead customer engagements and translate business requirements into technical architectures. Ensure compliance, security, and resiliency standards are embedded in all solutions. Key Skills & Experience Minimum 8 years of experience in cloud and infrastructure architecture. Strong experience in OpenStack components : Nova, Neutron, Cinder, Glance, Swift, etc. Deep domain expertise in at least one of the following: Cloud Infrastructure : Compute orchestration, virtualization, HA design. Storage : Block/Object storage solutions (Ceph, Swift, etc.). Networking : SDN, virtual networks, overlay networks, Neutron plugins. Proficient in container technologies and orchestration (Kubernetes is a plus). Experience with tools like Ansible, Terraform, or other automation frameworks. Familiarity with Linux internals, scripting, and system performance monitoring. Strong problem-solving, documentation, and customer-facing skills.
Key Responsibilities: Architect and implement container orchestration solutions using Kubernetes in production-grade environments. Lead the design and integration of OpenStack with Kubernetes-based platforms. Collaborate with infrastructure, DevOps, and software teams to design cloud-native applications and CI/CD pipelines. Define architectural standards, best practices, and governance models for Kubernetes-based workloads. Assess current system architecture and recommend improvements or migrations to Kubernetes. Mentor and guide junior engineers and DevOps teams on Kubernetes and cloud-native tools. Troubleshoot complex infrastructure and containerization issues. Key Requirements: 5+ years of experience in IT architecture with at least 4+ years working on Kubernetes. Deep understanding of Kubernetes architecture (control plane, kubelet, etcd, CNI plugins, etc.) Strong hands-on experience with containerization technologies like Docker and container runtimes. Proven experience working with OpenStack and integrating it with container platforms. Solid knowledge of cloud infrastructure, networking, and persistent storage in Kubernetes. Familiarity with Helm, Istio, service mesh, and other cloud-native tools is a plus. Experience with CI/CD pipelines, infrastructure as code (e.g., Terraform), and GitOps practices. Excellent problem-solving skills and ability to work in fast-paced environments. Preferred Qualifications: Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD) Experience with multiple cloud platforms (AWS, Azure, GCP, or private cloud) Background in networking or storage architecture is highly desirable.
Windows driver development - Job description: Looking for 3-5 years experienced Windows Device Driver Developer with strong C & C++ programming skills and in-depth knowledge of Windows driver development for Windows 11 and previous versions. The role requires working with WDM and WDF frameworks and developing and debugging drivers for x86 / ARM64 architecture. The candidate should also be comfortable with local and remote debugging. The current requirement is to develop a Windows driver for an AI Accelerator card (NPU) for neural network processing. Responsibilities include: Design, develop, and debug Windows device drivers using WDM and WDF frameworks. Perform remote debugging and troubleshoot drivers effectively, utilizing tools to ensure high performance and stability. Collaborate with hardware teams to ensure proper integration and performance of drivers on given (x86_64/ARM64) architecture. Apply knowledge of system registers in ARM and handle other low-level architecture-specific tasks. Skills Required: Proficiency in C and C++ Strong experience with WDM, WDF, UMDF, KMDF Windows 11 driver development expertise Strong debugging skills, including remote debugging of Windows drivers Very strong in developing PCIe based Windows device drivers and well equipped, comfortable with PCIe protocol specifications. Ability to port the driver functionality, and features from other OS to Windows Good understanding of x86_64/ARM64 architecture and system registers Excellent problem-solving abilities, attention to detail, and quality deliverables Preferred experience Previous experience working with cross-functional teams on HW & SW integration. Signing of kernel modules and deployment. Experience with version control systems (e.g., Git) and modern software development practices. Linux and/or other OS/RTOS device driver experience.
Roles and Responsibilities : Controller and Treasury 1. Leads the Corporate Finance function for India and is responsible for external and internal reporting of financial information including month end close process, annual audits including Board reporting. 2. Manage monthly close, audits and procurement process. 3. Strong familiarity with US GAAP/ IFRS based financial standards especially service revenue recognition. 4. Manage Treasury, payment gateway and Banking relationships. Business Finance and Taxation 5. Expertise with Financial Models, AOP and ability to model complex business scenarios. 6. Understanding of the unit level metrics. 7. Familiar with US and India taxes to ensure compliance and filings 1099, Use and Sales tax etc. and work with year-end CPA for filing returns. 8. Secretarial and Legal contracts– basic familiarity of time line and laws, work with CS firms Functional / Technical Skills 1. Chartered Accountant and have 6+ years of overall experience and 4 years in finance controllership/tax function. 2. Strong excel modelling skills is a must. 3. Hands on expertise on ERP Systems, process implementation and familiarity with technical accounting standards i.e. GAAP/ IFRS etc. 4. Clear understanding of Financial Planning, Financial Management, Budgeting, Forecasting, Compliances, Business Growth Strategy etc. 5. Maturity to influence key stake holders and work under pressure while ensuring quality output. 6. Excellent communication skills, ability to express complex and abstract ideas in a concise manner.
Job Description: Developing a software pipeline for end-to-end ML Model Inference for specific hardware accelerator by achieving maximum performance & accuracy. Implementing cutting edge deep learning layers for various model categories like CNN, RNN, LSTM, GANs, etc using customized inference pipeline for NN Processor. Performance optimization for inferencing the LLM Models in customized hardware with various layer types including transformer, encoder-decoder, etc based models. Hardware architecture aware and computation conscious implementation of solutions in an embedded device and maximize the throughput. Develop tools and applications by producing clean, efficient code. Identify, prioritize and execute tasks based on requirement. Implementation, Review, Debug code, Product Delivery and quick turn arounds. Collaborate with team to brainstorm and create new products. Mentor fresh joiners and foster team culture. Must-Have: BE/BTech/MS/MTech graduates with Computer science Engineering with 4+ yrs of experience. Solid programming experience in C/C++ with proven experience as Senior Software Engineer. Experience in implementing kernel intrinsics for Machine Learning or Computer Vision algorithms with a focus on optimization. Extensive experience in software development and project management. Strong analytical and problem-solving skills. Adaptable to execute complex tasks, under tight schedules and dynamic conditions. Familiarity with various operating systems (Linux, Mac OS, Windows). Ability to work independently and manage a team. Excellent organizational and leadership skills. Working knowledge on Deep Learning frameworks (Like ONNX, TensorFlow, PyTorch or Any Hardware Accelerator Software Pipeline Experience). Nice-to-Have: Knowledge in Python. Experience in managing team size of 4 or more. Experience Working in an Agile Environment. Experience in using automated testing frameworks.
4-8 years of hands-on experience in OpenBMC and data-model protocols between BMC services, e.g. MCTP, PLDM/PSDM, CXL, RedFish, RAS API Attends and is familiar with Open Compute Global Summit and its workgroups. Expert understanding of interfacing application layer, Kernel Layer and Hardware in OpenBMC SW architecture. Experience in Linux device drivers is an added advantage. Experience in controlling / retrieving from the datacenter servers from BMC. Expert level debugging throughout the workflow. Candidates should interface with customer for requirement gathering / analysis to derive the efforts, timeline and identify the risks, dependency and mitigate the challenges. While contributing individually, guide the team technically and move towards the right directions.
Role & responsibilities We are seeking an experienced GPU Programming Engineer to join our team. In this role, you will focus on developing, optimizing, and deploying GPU-accelerated solutions for high-performance machine learning workloads. The ideal candidate has strong expertise in GPU programming across one or more platforms (e.g., NVIDIA CUDA, AMD ROCm/HIP, or OpenCL) and is comfortable working at the intersection of parallel computing, performance tuning, and ML system integration. Key Responsibilities Develop, optimize, and maintain GPU-accelerated components for machine learning pipelines using frameworks such as CUDA, HIP, or OpenCL Analyze and improve GPU kernel performance through profiling, benchmarking, and resource optimization. Optimize memory access, compute throughput, and kernel execution to improve overall system performance on the target GPUs. Port existing CPU-based implementations to GPU platforms while ensuring correctness and performance scalability. Work closely with system architects, software engineers, and domain experts to integrate GPU-accelerated solutions. Preferred candidate profile Bachelor's or master's degree in computer science, Electrical Engineering, or a related field. 2+ years of hands-on experience in GPU programming using CUDA, HIP, OpenCL, or other GPU compute APIs. Strong understanding of GPU architecture, memory hierarchy, and parallel programming models. Proficiency in C/C++ and hands-on experience developing on Linux-based systems. Familiarity with profiling and tuning tools such as Nsight, rocprof, or Perfetto. Preferred Qualifications Familiarity with cuDNN, TensorRT, OpenCL, or other GPU computing libraries.