|
Sr. Platform Engineer- GenAI - Ann Arbor Michigan
Company: Disability Solutions Location: Ann Arbor, Michigan
Posted On: 11/20/2024
Base Pay Range: $103,000.00 - $175,100.00 AnnuallyPrimary Location: USA-MI-Ann Arbor-KLAKLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits identified below. Interns are eligible for some of the benefits identified below. Our pay ranges are determined by role, level, and location. The range displayed above reflects the minimum and maximum pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including location, job-related skills, experience, and relevant education level or training. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process. Company Overview KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us. Group/Division The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT's mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.Job Description/Preferred Qualifications - Identify and resolve infrastructure gaps to ensure reliable, efficient, and scalable solutions
- Develop advanced AI/ML infrastructure solutions that enhance the efficiency of our skilled ML teams
- Design and implement solutions for critical areas, including distributed storage systems, scheduling systems, high availability capabilities, and core reliability issues within our large-scale GPU clusters
- Monitor and optimize the performance of our AI/ML infrastructure, ensuring high availability, scalability, and efficient resource utilization
- Develop and deploy automation tools, monitoring solutions, and operational strategies to streamline infrastructure management and reduce manual tasks
- Work with various teams, including ML developers, data engineers, and DevOps professionals, to create a cohesive and integrated AI/ML infrastructure ecosystem
- Implement and manage GPU infrastructure within Kubernetes clusters to support high-performance computing and AI/ML tasks
- Deploy and manage open-source GenAI components, such as vector databases and various AI/ML models, ensuring seamless integration and optimal performance
- Evaluate and integrate new open-source GenAI tools and technologies to enhance the platform's capabilities
- Collaborate with the research and development teams to implement and optimize innovative AI/ML models and algorithms
- Ensure the security and compliance of open-source GenAI components within the infrastructure
- Leverage High-Performance Computing (HPC) experience to optimize and manage large-scale AI/ML workloads
- Design, implement, and manage on-premises, cloud, and hybrid-based ML platforms to support diverse AI/ML workloads and ensure flexibility and scalability Minimum Qualifications
|
|