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Hewlett Packard Enterprise is at the forefront of High Performance Computing and AI innovations to solve the most difficult and complex problems that we are facing today. In our Physics-Based GenAI team at Hewlett Packard Labs, we are dedicated to pushing the boundaries of what's possible with artificial intelligence. We specialize in creating cutting-edge machine learning algorithms and applications by augmenting state-of-the-art LLMs with concepts and tools from symbolic AI, physics simulators, statistical physics and non-equilibrium thermodynamics. We aim to revolutionize AI by creating first-principled generative models for system-2 thinking that can perform reliable and interpretable complex reasoning over multimodal data. Join us to be a part of a team that shapes the future of high-performance AI.
Job Responsibility:
Developing and refining AI models that can generate text, images, audio, or other types of symbolic, numerical, graphical, and scientific contents.
Work closely with a multidisciplinary team of engineers, researchers, and product managers.
Full development cycles of pre-training, fine-tuning, and inference to build efficient and innovative GenAI systems.
Requirements:
PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Electrical Engineering, Mathematics, or other related fields.
1 to 5 years relevant professional experience.
Minimum 3 years working experience with AI and machine learning, particularly in developing and deploying generative models.
Proven experience in software development with a strong background in algorithms, data structures, and object-oriented programming.
Proficiency in Python and C/C++.
Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch).
Excellent understanding of neural networks, deep learning, and generative models.
Ability to work in a fast-paced, iterative development environment.
Strong problem-solving skills, with a creative and analytical approach to tackling challenges.
Excellent communication skills, with the ability to collaborate effectively across diverse teams.
Nice to have:
Working experience with HPC programming environments.
Familiarity with combinatorial optimization techniques and algorithms, and their application in solving complex computational problems.
Background in computational physics, with an understanding of how physical principles can be applied to improve machine learning models and algorithms.
Experience in applying generative AI models to solve problems in areas such as material science, quantum computing, or complex system simulations.
Experience with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
Contributions to open-source AI/ML projects or publications in relevant fields.
Experience with containerization and orchestration technologies.
What we offer:
A competitive salary and extensive social benefits
Diverse and dynamic work environment
Work-life balance and support for career development
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