HPE Labs - AI/ML Research Engineer

HPE Labs - AI/ML Research Engineer

  

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

Job Description:

   

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 HPE Labs, we are dedicated to pushing the boundaries of what's possible with artificial intelligence. As a Research Engineer, 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.

Role and Responsibilities

• 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.

Qualifications and Education Requirements

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Mathematics, or other related fields.

• 3+ 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., TensorFlow, PyTorch).

• Deep understanding of machine learning algorithms and principles, especially in the context of generative AI.

• Strong mathematical background, with excellent skills in areas such as statistics, probability, linear algebra.

• Creative and analytical thinking abilities, with a passion for solving complex problems.

• Excellent communication skills, capable of conveying complex ideas clearly and engaging with both technical and non-technical audiences.

Preferred Skills

• Knowledge of computational physics, statistical physics, many-body physics simulations, or quantum computing, and how to apply these principles to develop innovative AI algorithms and models.

• Proficiency with hosting and operating locally generative AI models, through frameworks such as ollama, vllm,  etc

• Background in discrete optimization, combinatorial optimization, Monte Carlo methods, quantum-inspired algorithms, and applying these disciplines to enhance AI models.

• Programming experience in high-performance computing (HPC) environments.

• Experience with cloud computing platforms, GPU computing, or FPGA computing

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.

#unitedstates#highperformancecompute

Job:

Engineering

Job Level:

TCP_03

    

"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
– United States of America: Annual Salary USD 136,500 - 276,500 in California
The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

   

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

   

No Fees Notice & Recruitment Fraud Disclaimer

 

It has come to HPE’s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates.  These scammers often seek to obtain personal information or money from candidates.

 

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.  The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.