Ph D/Research Intern - AI Research Lab

Location: Bengaluru, Karnātaka, 560048 Department: Administration & Workplace

Ph D/Research Intern - AI Research Lab

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week 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 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.

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.

What We Can Offer You

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 divi