Ph D/Research Intern - AI Research Lab

Ph D/Research Intern - AI Research LabThis role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Job Description:

Role:

Roles and Responsibilities:

We are seeking candidates interested in research and development of advanced technologies in Trustworthy Agentic AI and Generative AI based Foundation Model systems. A particular focus of this internship is designing AgenticOS and related algorithms, and evaluations. The intern will work at the intersection of machine learning and systems to define and prototype novel learning abstractions and mechanisms that define the AgenticOS and make agentic AI reliable, shareable, scalable, and evolvable, particularly for long horizon applications. This could include Data Centric AI techniques that capture, management, search, enhancement and interpretation of metadata and lineage for AI pipelines that enable reproducibility, reuse and optimization of pipelines; discovery, selection and usage of relevant high quality data for trustworthy AI outcomes across multiple AI applications; and development, evaluation and testing of Foundation AI models for different modalities: Natural Language Processing - NLP, Large Language Models - LLM, Time Series Forecasting and Anomaly Detection, VLMs, Diffusion models, AI for Science, etc.; multi-modal Retrieval Augmented Generation workflows; and advanced chain-of-thought, meta-reasoning, reinforcement learning and cognitive methods.

We are particularly interested in individuals with a background in computer systems, machine learning, deep learning, statistics, generative AI, data management, and big data pipelines, with good understanding of the current state of the art, and a demonstrated track record in innovative research. The ideal candidate can thrive in an applied research environment, balancing significant technical contributions published externally in open source with the hands-on engineering skill to bring such contributions to practice in partnering with our internal software development teams and external partners. Our preference is for 6 months long commitment, however, we will consider 3 months long internship for outstanding candidates who are unable to commit to 6 months.

Qualification and Educational Requirements:

Second or later year PhD student in Computer Science or related fields with a focus on data engineering and data science, in particular Machine Learning, Deep Learning, Generative AI and/or data management for AI.

Preferred Skills:

• Strong programming skills in Python, with high proficiency in data structures and algorithms
• Outstanding analytical and problem-solving skills
• Experience with Generative AI: Large Language Models (LLMs), Diffusion Models, RAG, Chain of Thought, etc.
• Experience in AI model development lifecycle, ML/deep learning frameworks and MLOps platforms (e.g. Pytorch/Tensorflow, MLFlow, Kubeflow)
• Experience building or researching agentic AI systems, such as LLM-based agents, tool use, multi-agent orchestration, and agent frameworks and protocols (e.g., MCP, A2A)
• Experience in GPU and CPU acceleration, and Model Optimization – a plus
• Expertise in research of data and workflow management systems – a plus
• Experience in system software performance and scalability optimization – a plus
• Experience with multi-threaded programming, parallel processing, OOD/OOP/distributed programming – a plus
• Experience in containerized development and orchestration tools (e.g. Kubernetes, Ezmeral) – a plus
• Experience with hybrid AI-HPC workflows (e.g., AI surrogate modeling, computational steering of experiments) – a plus
• Familiarity with agent memory, state management, and long-horizon execution (e.g., context management, checkpointing, recovery) – a plus
• Background in operating systems, scheduling, resource management, or LLM/agent serving and inference systems – a plus
• Experience with trust, safety, security, observability, or provenance for autonomous agents – a plus
• Experience designing benchmarks, simulators, or evaluation methodologies for agentic systems – a plus
• Demonstrated ability to work across machine learning and systems, with publications or open-source contributions in either area – a plus

Accessibility

HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.

Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

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.

Job:

Administration

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N/A

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