Cloud Solution Engineer - GPU/Gaudi AI Accelerator

Job Description

Do you want to innovate an industry-leading developer cloud? The cloud development team within the Software and Advanced Technology Group (SATG) is developing and shaping the way people think about computing by focusing on developers, ecosystem partners, academia, etc. We are redefining the space with cutting-edge software technologies along with industry-leading CPU, GPU, AI accelerator, and IPU hardware. Join us if you want to make history, provide innovative solutions to challenging engineering problems, and challenge the state-of-the-art in cloud technologies.

Responsibilities

• Design and implement cloud solutions that leverage Intel technologies and Gaudi AI accelerators or GPU, with a focus on LLM applications.
• Work closely with AI researchers and developers to understand their cloud infrastructure needs for LLM development and deployment.
• Keep up-to-date with advancements in LLMs, including training techniques, optimization, and deployment in cloud environments.
• Integrate Intel's development tools and libraries to support the development and scaling of LLMs in the cloud.
• Advocate for the Intel Developer Cloud services and the use of Gaudi AI accelerators through technical discussions and developer support.
• Provide technical leadership and mentorship within project teams, promoting best practices in cloud architecture and AI.
• Analyze emerging trends in cloud computing and AI, especially LLMs, to guide the development of Intel Developer Cloud services.
• Provide a White Glove support service experience to customers.
• Work effectively with Site Reliability Engineering to drive requirements for monitoring and alerting to meet service uptime requirements.

Qualifications

Minimum Qualifications

• Bachelor's degree in Electrical/Computer Engineering or Computer Science and 6+ years of experience, OR a Master's degree in Electrical/Computer Engineering or Computer Science and 4+ years of experience, OR a PhD in Electrical/Computer Engineering or Computer Science and 2+ years of experience in:
  • Building cloud or cluster computing infrastructure
  • Hands-on debugging of live production systems
  • Cloud architecture
  • AI performance engineering

Preferred Qualifications

• 5+ years in customer-facing solution engineering related functions
• 3+ years in systematically optimizing workloads in large cluster infrastructure
• Experience with Intel hardware and software, including Gaudi AI accelerators, and familiarity with LLMs.
• A track record of designing and deploying cloud solutions for AI applications, emphasizing scalability, performance, and security.
• Knowledge of current LLM frameworks and tools, and their implementation in cloud platforms.
• Proficiency in cloud service models, virtualization, container orchestration, and cloud-native technologies.
• Skilled in scripting, automation, and Infrastructure as Code (IaC) tools.
• Excellent communication skills and the ability to work collaboratively within a team environment.
• Relevant certifications in cloud computing, AI, or machine learning are desirable.

Inside this Business Group

Enable amazing computing experiences with Intel Software continues to shape the way people think about computing – across CPU, GPU, and FPGA architectures. Get your hands on new technology and collaborate with some of the smartest people in the business. Our developers and software engineers work in all software layers, across multiple operating systems and platforms to enable cutting-edge solutions. Ready to solve some of the most complex software challenges? Explore an impactful and innovative career in Software.

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as benefit programs which include health, retirement, and vacation.

Working Model

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. In certain circumstances, the work model may change to accommodate business needs.