59 Ml Platforms Jobs

As a Senior Manager of Technical Program Management at Capital One India, you will be part of the Machine Learning Experience (MLX) team, a group dedicated to implementing responsible ML models and features across the company. Your role will involve collaborating with various teams including product, engineering, and data scientists to create roadmaps, define milestones, and build scalable ML products and platforms. You will be responsible for driving innovation, presenting to executive stakeholders, and ensuring the successful delivery of enterprise-level initiatives. The ideal candidate for this role will possess a strong technical background in building scalable platforms and products, along with exceptional communication and collaboration skills. You should have a quantitative approach to problem-solving, the ability to simplify complex technical concepts, and a focus on execution and results. Emotional intelligence, empathy, and the ability to lead a program team are also key attributes for success in this role. In terms of qualifications, a Bachelor's degree is required, along with at least 5 years of experience managing technical programs and designing data-intensive solutions. Experience with machine learning, cloud infrastructure, and major ML frameworks such as XGBoost and PyTorch is highly desirable. Additionally, familiarity with Agile delivery, building distributed systems, and working within a highly regulated environment are preferred qualifications. If you meet these qualifications and are looking to join a dynamic team at Capital One India, we encourage you to apply for the Senior Manager - Technical Program Management position. Please note that Capital One is an equal opportunity employer committed to non-discrimination and promotes a drug-free workplace. If you require any accommodations during the application process, please contact Capital One Recruiting for assistance.,

As a Visionary System Design at our organization, you will have the exciting opportunity to architect the foundation of what could potentially be the first true productized Artificial General Intelligence (AGI). You will collaborate closely with passionate individuals across various departments including product, research, and operations. Your problem-solving skills will be put to the test as you navigate complexity and view it as a canvas for innovation. Effective communication and collaboration will be key as you inspire clarity amidst chaos and drive alignment towards ambitious goals. Your experience in scalable engineering leadership will be essential in building platforms that can scale across data, people, and purpose, ultimately contributing to making the world a better place through technology. The ideal candidate for this role will not only be responsible for designing and scaling the core architecture of this ambitious initiative but also for nurturing and leading a high-performance engineering team. You must possess deep technical expertise in systems design, machine learning infrastructure, and product engineering. Additionally, the ability to collaborate effectively with research scientists, product teams, and executive leadership is crucial for success in this position. **Responsibilities:** - **Technical Strategy & Architecture:** Design a future-ready, modular, and scalable platform to support AGI research, deployment, and iteration. - **Team Leadership:** Recruit, develop, and lead a top-tier engineering team specializing in systems, infrastructure, tooling, and ML integration. - **Collaboration with Research:** Translate research advancements into robust, production-grade engineering systems. - **Platform Engineering:** Develop APIs, frameworks, and services that transform AGI capabilities into usable product modules. - **Security & Ethics by Design:** Ensure that systems are secure, ethical, and in alignment with responsible AI development practices. - **Innovation Ownership:** Identify opportunities for innovative approaches to large-scale data handling, knowledge representation, and computation. - **Cross-functional Leadership:** Collaborate with Product, Design, and Strategy teams to define features, roadmap, and key performance indicators (KPIs). **Qualifications:** - **Degree:** B.Tech / M.Tech / PhD in Computer Science, Electrical Engineering, or related field. - **Experience:** Minimum of 10 years in software engineering, with at least 3 years in technical leadership roles overseeing platform/infrastructure for ML or distributed systems. - **Expertise:** Demonstrated ability to architect systems at scale including distributed computing, real-time data pipelines, model serving, and orchestration. - **Tools:** Proficiency in Kubernetes, ML platforms (e.g., Ray, JAX, PyTorch), CI/CD, and cloud-native architecture. - **AGI-Aligned Vision:** Strong grasp of ML/AI fundamentals and a commitment to co-create responsible and impactful AGI. If you are a candidate who thrives in challenging environments, values diversity and inclusivity, and enjoys working in a dynamic and slightly unconventional setting, we encourage you to apply. We are looking for individuals who resonate with our organizational values and culture, and who share our dedication to excellence. Join us on this exciting journey by submitting your application now!,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.