Hewlett Packard Labs Senior AI​/ML Research Scientist

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This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next.

We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

While generative AI models, such as Large Language Models (LLMs) and diffusion models, have reached unprecedented results, they are inefficient and lack interpretability, especially when involved in complex reasoning and scientific computing. In the Emergent Machine Intelligence Team at Hewlett Packard Labs, we are dedicated to pushing the boundaries of what's possible with artificial intelligence. As a Senior Research Scientist, you will be at the forefront of our efforts to develop groundbreaking generative AI models.

You will be crafting cutting-edge algorithms and applications by augmenting state-of-the-art LLMs with extensive test-time compute, adopting tools from symbolic AI, incorporating physics simulators, and employing insight from statistical physics and non-equilibrium thermodynamics. You will work closely with a multidisciplinary team of engineers, researchers, and product managers, during full development cycles of pre-training, fine-tuning, and inference. Together, our goal is to build scalable, efficient, and innovative generative AI systems.

Join us to be a part of a team that shapes the future of high-performance AI.

• Conduct high-quality research in generative AI, including but not limited to designing algorithms for pre-training and post-training current autoregressive and diffusion models for multimodal data.
• Design, implement, and validate new algorithms and models for augmented LLMs, pushing the boundaries of AI capabilities.
• Developing and prototyping novel algorithms for fine-turning, retrieval augmented generation, and in-context learning for various generative models.
• Developing algorithms for training and inference in Energy-Based Models.
• Collaborate with cross-functional teams to apply research findings to develop new products or enhance existing ones.
• Publish research papers in top-tier journals and conferences, sharing findings with the broader scientific community.
• Stay abreast of the latest AI research and trends, identifying opportunities for innovation and improvement.
• Mentor junior researchers and engineers, fostering a culture of knowledge sharing and collaboration.
• Develop prototypes and proof-of-concept implementations to demonstrate the potential of research findings.
• Engage with the academic community by attending conferences, workshops, and seminars.

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Mathematics, or other related fields.
• 5+ years working experience with training and fine-tuning generative AI models including LLMs, diffusion models, or Energy-Based Models
• Experience with test-time compute techniques, such as chain-of-thoughts, self–consistency, or reinforcement learning based verifiers, etc.
• Proven track record of research in generative models, demonstrated through first tier publications (e.g., NeurIPS, ICML, ICLR, or high impact journals), patents, or publicly available projects.
• Proficiency in programming languages commonly used in AI research, such as Python, and experience with AI/ML frameworks (e.g., Tensor Flow, PyTorch).
• Deep understanding of machine learning algorithms…