Hewlett Packard Labs - Machine Learning Research Scientist - Early Career

Hewlett Packard Labs - Machine Learning Research Scientist - Early Career

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Location : Milpitas, California, United States of America

Time Type : Full time

Posted On : Posted 2 Days Ago

Job Requisition ID : 1181363

This role has been designed as ‘Onsite’ with an expectation that you will primarily work from an HPE office.

Who We Are :

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 diverse 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.

Job Description :

We are currently seeking highly qualified, self-motivated candidates to accelerate research towards new applications, core methodologies, and technologies in Artificial Intelligence at Hewlett Packard Labs.

Hewlett Packard Labs is an international research organization with its headquarters and largest facility located in Milpitas, California. As the central research organization for Hewlett Packard Enterprise (HPE), Hewlett Packard Labs' purpose is to deliver breakthrough technologies and technology advancements that provide a competitive advantage for the company, by investing in fundamental science and technology in areas of interest to HPE and getting the resulting technologies ready for adoption into new and existing markets.

The Artificial Intelligence Research Lab focuses on researching and developing technologies, architectures, and software to develop cutting-edge solutions in key areas of Deep Learning and Machine Learning, including Reinforcement Learning and Natural Language Processing. This is a unique opportunity to work at a start-up pace within a big company. We are looking for an entrepreneurial mindset and a deep passion to take a ML problem and conduct research and come up with a solution with a fast turnaround time.

This is an office-based role and the selected candidate will be working from HPE office in Milpitas, CA.

Role and Responsibilities

This research scientist position is with the AI research team at Hewlett Packard Labs, HPE’s core research organization based in the San Francisco Bay Area. The team has made significant contributions in areas like reinforcement learning for complex systems, trustworthy AI, large language models (LLMs), optimizations, and digital twins, with a proven record of award-winning publications in top machine learning venues.

As part of this cutting-edge core AI research team, you’ll help bridge research and real-world applications, addressing major challenges such as supercomputing sustainability, nuclear fusion, and the trustworthiness of LLMs. Your responsibilities will include conducting research, developing solutions, and creating intellectual property in emerging fields like reinforcement learning, LLMs, digital twins, clean energy, data center optimization, and sustainability. This will involve developing advanced technologies for analysis, optimization, time series forecasting, uncertainty quantification, and control, with innovation and technology transfer.

You’ll be expected to provide thought leadership, collaborate internally and externally, and contribute to HPE’s strategy by identifying emerging technologies. The role involves publishing in top conferences like NeurIPS, AAAI, and ACL, as well as developing patent applications. With this hands-on role, you’ll engage in software development, GPU acceleration, model optimization, and real-time data streaming to create robust AI solutions for real-world use cases. This position offers the unique opportunity of both AI research and applications, with high-impact projects with external and internal collaborators.

Qualifications and Education Requirements

PhD in Computer Science, Electrical Engineering, or related fields focusing on Machine Learning for the dissertation.

Extensive experience in deep learning research is required, preferably in Large Language Models or Reinforcement Learning .

Experience developing applications with deep learning frameworks like PyTorch with a high software proficiency.

Preferred Skills

Experience in research and development in Large Language Models.

Experience in research and development in Reinforcement Learning and / or Digital Twins.

Experience and deep knowledge of different deep learning model architectures for time series, uncertainty quantification, optimization, and control.

Strong programming skills in Python, data structures, and algorithms are required.

Experience with ML model optimization, GPU acceleration, heterogeneous computation, system software, and performance optimization desired.

Experience in Python Web Frameworks – Django, Flask - a plus but not required.

Join us and make your mark!

We offer :

• A competitive salary and extensive social benefits
• Diverse and dynamic work environment
• Work-life balance and support for career development
• An amazing life inside the element!

Want to know more about it? Then let’s stay connected!

HPE is an Equal Employment Opportunity / Veterans / Disabled / LGBT and Affirmative Action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together.

Accommodation of special needs for qualified candidates may be considered within the framework of the HPE Accommodation Policy.

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