Hewlett Packard Enterprise - Houston, TX
posted about 2 months ago
Hewlett Packard Enterprise (HPE) is seeking a Senior AI and Machine Learning Engineer to join our High Performance Computing, AI and Labs team. This role is primarily remote, allowing you to work from home while contributing to innovative solutions that accelerate our customers' digital transformation. As a global edge-to-cloud company, HPE is dedicated to helping organizations connect, protect, analyze, and act on their data and applications, enabling them to derive insights and outcomes swiftly in today's complex environment. Our culture is built on collaboration, diversity, and the pursuit of excellence, making it an ideal place for professionals looking to grow their careers. In this position, you will focus on enhancing the performance of Large Language Models on HPE GPU servers, conducting system-level analyses of HPC and AI workloads across various HPE platforms. You will run machine learning and deep learning code on advanced hardware, including NVIDIA and AMD GPUs, and high-speed networks like InfiniBand. Your responsibilities will also include developing software and scripts to automate AI workloads, installing and configuring complex IT infrastructure components, and documenting performance data to understand workload behavior. You will communicate your findings effectively to both technical and non-technical colleagues, mentor junior staff, and collaborate with software and hardware partners to optimize systems and resolve performance issues. This role requires a strong educational background, typically a Master's degree or PhD in Computer Science, Engineering, Information Technology, or a related field, along with at least three years of relevant experience in machine learning and artificial intelligence. You will need proficiency in AI and machine learning frameworks such as TensorFlow, PyTorch, and ONNX, as well as experience with high-performance computing servers and networking. Strong analytical skills and the ability to work independently in a semi-remote setting are essential for success in this role.