AI and Machine Learning Engineer III

AI and Machine Learning Engineer III

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

Management Level Definition

Contributions include applying developed machine-learning subject matter expertise to solve common and sometimes complex technical problems, and recommending alternatives where necessary. An example is balancing answer quality, latency, cost, energy, and carbon in hybrid LLM systems. Might act as project lead for research prototypes and provide assistance to lower-level professionals and interns. Exercises independent judgment and consults with researchers, engineers, and platform partners to determine the best method for accomplishing work and achieving objectives.

Responsibilities

• Participates as a member of the Hewlett Packard Labs Machine Learning research team, carrying out the investigation, design, development, execution, and implementation of AI tokenomics research to generate new products, technologies, and intellectual property.
• Researches and prototypes methods that learn representations of jobs and system states, and that predict workload complexity, answer quality, latency, token demand, energy, and cost.
• Develops routing policies, model cascades, and adaptive controllers that select the appropriate LLM, reasoning mode, retrieval strategy, tool chain, and deployment target (local, edge, private cloud, or public cloud) for each job.
• Develops methods to assign and enforce token, context, reasoning, and compute budgets based on job difficulty, priority, risk, service-level objectives, and expected business value.
• Builds benchmark, telemetry, accounting, and workload-simulation environments.
• Conducts controlled experiments, ablation studies, sensitivity analyses, and stress tests across model families, hardware platforms, and deployment environments. Evaluations measure answer quality, routing accuracy, token efficiency, tail latency, throughput, reliability, cost per completed job, energy per token, and carbon per completed job. Communicates results to team members for review and feedback.
• Collaborates with internal and external researchers and engineers to validate results, and helps transfer promising technologies into HPE AI platforms.
• Prepares papers and presentations for peer review, publication, and delivery at leading ML conferences and industry events. Creates patent disclosures and supporting documentation.

Education and Experience Required

• PhD completed or expected soon in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field, with a research focus in machine learning.
• Typically 4 years of experience, including graduate and doctoral research.

Knowledge and Skills

• Strong foundation in deep learning, optimization, probabilistic modeling, reinforcement learning, or related machine-learning methods, demonstrated through doctoral research, internships, or publications.
• Ability to implement and evaluate research ideas in Python using frameworks such as PyTorch, with sound experimental and software-engineering practices.
• Application of experimental design, benchmarking, ablation studies, and statistical analysis to collect, validate, and analyze research data.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to effectively communicate research plans, proposals, and results, and negotiate options at management levels.

Preferred

Qualifications

• Research experience with ML, LLMs, model routing, reinforcement learning, causal inference, constrained optimization, retrieval-augmented generation, or agentic AI.
• Interest or experience in token-efficient inference, per-job compute budgeting, multi-model serving, or edge-to-cloud AI systems.
• Interest or experience in sustainable AI, energy-aware computing, or carbon-aware scheduling and optimization.

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 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.

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