| Senior AI Infrastructure Engineer at San Diego, California, USA |
| Email: [email protected] |
| From: g vamshi, 3ktechnologies [email protected] Reply to: [email protected] Job Title: Senior AI Infrastructure Engineer (Data Center for AI Projects) Location: San Diego, CA Client: ASML Duration: Long Term About ASML: ASML is a leader in the semiconductor industry, providing advanced lithography machines that are integral to the production of chips for global technology companies. Our team in San Diego focuses on innovative solutions in the field of AI to enhance efficiency, performance, and scalability. We are looking for a highly skilled Senior AI Infrastructure Engineer to support and advance our AI projects through the development of robust data center infrastructure. Job Description: As a Senior AI Infrastructure Engineer at ASML, you will be responsible for designing, deploying, and managing AI-specific infrastructure within a data center environment. This role requires deep expertise in large-scale, high-performance computing, with a focus on meeting the unique demands of artificial intelligence workloads. You will work closely with AI engineers, IT teams, and data scientists to ensure the AI infrastructure is optimized for maximum performance and scalability. Key Responsibilities: 1.Design & Deployment: Architect and implement state-of-the-art data center infrastructure tailored for AI/ML workloads, including compute, storage, networking, and GPU-based resources. 2.Infrastructure Management: Oversee the deployment, configuration, and management of hardware and software components critical to AI infrastructure. Ensure uptime, reliability, and scalability of resources. 3.Performance Optimization: Continuously monitor, benchmark, and optimize the performance of AI models running on the data center infrastructure, focusing on workload distribution and resource allocation. 4.AI Workload Automation: Develop and implement automation strategies to streamline the deployment, orchestration, and scaling of AI models across distributed systems. 5.Collaboration: Partner with cross-functional teams, including AI engineers, software developers, IT operations, and data scientists to align AI infrastructure with project needs and business goals. 6.Security & Compliance: Ensure the infrastructure complies with industry standards and company security policies, implementing solutions that protect sensitive AI data and models. 7.Innovation & Improvement: Stay abreast of the latest advancements in AI infrastructure technologies and data center management, recommending and implementing innovative solutions to drive operational efficiency. Qualifications: Experience: 1.Minimum of 7-10 years of experience in infrastructure engineering, with at least 5 years specifically in AI infrastructure and data center environments. 2.Proven experience designing and managing high-performance computing (HPC) environments with a focus on AI/ML workloads. 3.Hands-on experience with GPU-based computing, distributed systems, and scalable AI infrastructure. Technical Expertise: 1.Strong proficiency with data center infrastructure, including server hardware, storage solutions (e.g., NAS, SAN), networking, and cooling systems. 2.Experience with cloud platforms (AWS, GCP, Azure) and hybrid cloud solutions for AI projects. 3.Familiarity with container orchestration tools like Kubernetes, Docker, and infrastructure automation tools (e.g., Ansible, Terraform). 4.Deep understanding of AI/ML frameworks such as TensorFlow, PyTorch, and their integration with infrastructure. Education: Bachelors or Masters degree in Computer Science, Electrical Engineering, or a related field. A focus on AI/ML infrastructure is highly preferred. Skills: 1.Strong problem-solving abilities and a deep understanding of AI infrastructure challenges. 2.Excellent communication and collaboration skills, with the ability to work across multidisciplinary teams. 3.Experience with monitoring tools (e.g., Prometheus, Grafana) for infrastructure health and performance metrics. 4.Certifications: Relevant certifications in data center management (CDCP, CDCS) or cloud platforms (AWS Certified Solutions Architect, Google Cloud Certified) are a plus. Preferred Qualifications: 1.Experience with AI accelerator hardware (e.g., TPUs, custom ASICs). 2.Familiarity with cutting-edge AI infrastructure technologies, such as AI-specific compute clusters or high-bandwidth interconnects. 3.Prior experience working in a semiconductor or technology-heavy environment. Thanks & Regards Ganji Vamshi Bench sale / Technical Recruiter 1114 Cadillac Ct, Milpitas, CA 95035 3K Technologies, LLC www.3ktechnologies.com [email protected] Analytics | BI | Big Data | Cloud |Software Engg. Keywords: artificial intelligence machine learning business intelligence information technology California Connecticut Senior AI Infrastructure Engineer [email protected] |
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| Tue Oct 29 23:07:00 UTC 2024 |