Research Associate Intern (Networking and Distributed Systems Lab)

Hewlett Packard Enterprise•Milpitas, CA

43d•$43 - $93•Onsite

About The Position

Hewlett Packard Enterprise advances the way people live and work. We bring together the brightest minds to create breakthrough technology solutions, helping our customers make their mark on the world. At HPE we believe in bold moves, the power of “Yes we can”, and being a force for good. Our work thrives on differences, fueling creativity to give our customers all they deserve. But our work is far from over. In fact, we continuously push for better. We empower our team members to make an impact on our business and in the world while fostering a culture that is unconditionally inclusive. Whether you’re looking for an internship or to start your professional career, at HPE you’ll be able to create and collaborate on projects that challenge and inspire you. Hewlett Packard Labs are committed to the fast and seamless transfer of advanced technologies into next generation products and solutions; enabling the delivery of advanced Hybrid IT and IoT solutions for our customers. We are currently seeking highly qualified and self-motivated PhD/MS students for Internship positions in the Networking and Distributed Systems Lab at Hewlett Packard Labs in Milpitas, CA. The successful candidate will join NDSL and contribute to various cutting-edge areas: Cloud/Serverless computing: involving cloud management and monitoring, security, mobile cloud, scalability, and performance. Cloud/Datacenter networks: including aspects of management, routing, scalability, and security. High Performance Computing Fabrics: including HPE Slingshot and Ultra Ethernet technologies and aspects of congestion management, multipathing, in network telemetry and network collectives. AI and ML workload acceleration: exploring innovative ways to enhance AI and ML performance. WiFi-Cellular Convergence: contributing to the seamless integration as well as advancement of WiFi (WiFi 6/7 and beyond) and private/public cellular (5G/B5G) technologies. Edge-to-Cloud Infrastructure: shaping the future of edge and cloud interactions. Sustainability and Carbon Emission Reduction: Exploring efficient data center management and scheduling techniques, as well as innovations to enhance power grid security, reducing carbon emissions. Emerging disaggregated systems: enabling hardware and software supports for disaggregated systems including memory, storage, and accelerators. Additionally, we value expertise in the following domains: Network programmability: proficiency in developing programmable networks, application offloading, and RDMA. SmartNICs: experience with Smart Network Interface Cards, leveraging their capabilities for improved network performance and management. Containerized platforms: familiarity with containerized platforms, enabling efficient deployment, scheduling, and management of applications. GPU virtualization techniques: knowledge of techniques that optimize GPU usage through virtualization (e.g., MPS, MIG). Wireless Communication/Sensing: Knowledge of wireless communication protocols (WiFi/cellular), wireless sensing techniques (FTM/ToF/CSI), and/or wireless standards (IEEE 802.11/3GPP) AI/ML Development Frameworks and Programming tools: Familiarity with tool chains like PyTorch 2.0, Torch FX, JAX, TensorFlow and CUDA programming Compute Express Link (CXL) and storage systems: experience with CXL and storage systems such as NVMe, Container Attached Storage (CAS), File systems, Object storage, Key-value storage.

Requirements

Must be pursuing Ph.D./MS (or equivalent post-graduate degree) in Computer Science, Electrical Engineering, or relevant studies.
Strong research, analytical, and system-building skills are required; published articles are a definite plus.
Experience with implementation and system building, particularly in the areas of AI operations, cloud, and distributed systems.
Proficiency in making impactful presentations to key stakeholders, both verbal and written.
Ability to work independently and collaboratively within teams.

Nice To Haves

Network programmability: proficiency in developing programmable networks, application offloading, and RDMA.
SmartNICs: experience with Smart Network Interface Cards, leveraging their capabilities for improved network performance and management.
Containerized platforms: familiarity with containerized platforms, enabling efficient deployment, scheduling, and management of applications.
GPU virtualization techniques: knowledge of techniques that optimize GPU usage through virtualization (e.g., MPS, MIG).
Wireless Communication/Sensing: Knowledge of wireless communication protocols (WiFi/cellular), wireless sensing techniques (FTM/ToF/CSI), and/or wireless standards (IEEE 802.11/3GPP)
AI/ML Development Frameworks and Programming tools: Familiarity with tool chains like PyTorch 2.0, Torch FX, JAX, TensorFlow and CUDA programming
Compute Express Link (CXL) and storage systems: experience with CXL and storage systems such as NVMe, Container Attached Storage (CAS), File systems, Object storage, Key-value storage.