Description
OCI (Oracle Cloud Infrastructure) AI Infrastructure is at the forefront of building a cutting-edge, ultra-high-performance GPU platform designed to support AI/ML/HPC workloads. This is your chance to be part of the AI revolution, creating systems that allow customers to scale from tens to thousands of GPUs without compromising performance.
Our team is the GPU Availability and Monitoring team in the Compute Org. we are responsible for designing and developing architectural changes for GPU delivery, health monitoring, triage automation, and diagnostic services. These are essential for running distributed AI/ML/HPC workloads across thousands of GPUs, leveraging technologies like RoCE and Infiniband.
We're excited to meet a talented Senior Software Engineer like you, who shares our enthusiasm for innovation and excellence. As a valued member of our software engineering division, you'll have the opportunity to shape the future of our technology stack and drive meaningful change in the world of cloud infrastructure and automation.
In this role, you'll design, develop, troubleshoot, and debug software programs for databases, applications, tools, networks, and other cloud infrastructure components. Your expertise in AI and ML will help us stay ahead of the curve, and your passion for collaboration will inspire our team to achieve greatness together.
If you're ready to unleash your full potential and make a lasting impact, we'd love to hear from you!
Internal Responsibilities
Responsibilities
- Work independently in ambiguous situations to ensure adherence to published standards and practices.
- Design, develop, troubleshoot, and debug software programs for various cloud infrastructure components, including databases, applications, tools, and networks.
- Take an active role in defining and evolving standard practices and procedures for software engineering, with a focus on AI-driven development.
- Define and develop software for tasks associated with developing, designing, and debugging software applications or operating systems, leveraging AI and ML techniques.
- Lead the development of critical initiatives, including:
- Design and implement spike detection mechanisms for provisioning failures to minimize operational disruptions using ML algorithms.
- Expand integrations with Kafka to enable near real-time actions supporting 1-Day SLO objectives for hardware repairs, utilizing event-driven architecture and stream processing.
- Developing an automated ticket routing framework to streamline workflows, enhance efficiency, and reduce operational overhead, powered by NLP and ML.
- Accelerate dedicated initiatives through collaborative efforts with cross-functional teams and customers, applying AI-driven insights and recommendations.
- Harness the power of AI and ML to create innovative tools and frameworks that automate testing, simulate complex environments, and reproduce incidents, freeing up human ingenuity to focus on higher-value tasks and amplifying our ability to deliver exceptional customer experiences.
- Collaborate and lead technical discussions across multiple teams to ensure seamless integrations and effective problem-solving.
- Provide direction and mentoring to junior engineers, sharing knowledge and expertise to promote growth and development.
Technical Skills:
- Programming languages: Python, Java, TypeScript
- Development methodologies: Agile Principles
- Data management: data modeling, data warehousing, data governance
- Cloud infrastructure: OCI, AWS, Azure, Google Cloud Platform (GCP)
- Operating Systems: Linux, MacOS
- Scripting languages: Bash, Perl, Ruby
- Familiarity with containerization technologies such as Docker
- API design and development: RESTful APIs, API gateways, API security
- Familiarity with API documentation tools such as Swagger/OpenAPI
- Experience with AI-powered tools and platforms: chatbots, virtual assistants, predictive analytics
External Responsibilities
Responsibilities
- Work independently in ambiguous situations to ensure adherence to published standards and practices.
- Design, develop, troubleshoot, and debug software programs for various cloud infrastructure components, including databases, applications, tools, and networks.
- Take an active role in defining and evolving standard practices and procedures for software engineering, with a focus on AI-driven development.
- Define and develop software for tasks associated with developing, designing, and debugging software applications or operating systems, leveraging AI and ML techniques.
- Lead the development of critical initiatives, including:
- Design and implement spike detection mechanisms for provisioning failures to minimize operational disruptions using ML algorithms.
- Expand integrations with Kafka to enable near real-time actions supporting 1-Day SLO objectives for hardware repairs, utilizing event-driven architecture and stream processing.
- Developing an automated ticket routing framework to streamline workflows, enhance efficiency, and reduce operational overhead, powered by NLP and ML.
- Accelerate dedicated initiatives through collaborative efforts with cross-functional teams and customers, applying AI-driven insights and recommendations.
- Harness the power of AI and ML to create innovative tools and frameworks that automate testing, simulate complex environments, and reproduce incidents, freeing up human ingenuity to focus on higher-value tasks and amplifying our ability to deliver exceptional customer experiences.
- Collaborate and lead technical discussions across multiple teams to ensure seamless integrations and effective problem-solving.
- Provide direction and mentoring to junior engineers, sharing knowledge and expertise to promote growth and development.
Technical Skills:
- Programming languages: Python, Java, TypeScript
- Development methodologies: Agile Principles
- Data management: data modeling, data warehousing, data governance
- Cloud infrastructure: OCI, AWS, Azure, Google Cloud Platform (GCP)
- Operating Systems: Linux, MacOS
- Scripting languages: Bash, Perl, Ruby
- Familiarity with containerization technologies such as Docker
- API design and development: RESTful APIs, API gateways, API security
- Familiarity with API documentation tools such as Swagger/OpenAPI
- Experience with AI-powered tools and platforms: chatbots, virtual assistants, predictive analytics
