AI and Machine Learning Engineer III

We are seeking an experienced AI and Machine Learning Engineer III to join our team. As a member of the Hewlett Packard Labs Machine Learning research team, you will carry out investigations, designs, developments, executions, and implementations of AI tokenomics research to generate new products, technologies, and intellectual property.

Responsibilities:

• Participate in the investigation, design, development, execution, and implementation of AI tokenomics research
• Research and prototype methods that learn representations of jobs and system states, and that predict workload complexity, answer quality, latency, token demand, energy, and cost
• Develop routing policies, model cascades, and adaptive controllers that select the appropriate LLM, reasoning mode, retrieval strategy, tool chain, and deployment target for each job
• Develop methods to assign and enforce token, context, reasoning, and compute budgets based on job difficulty, priority, risk, service-level objectives, and expected business value
• Build benchmark, telemetry, accounting, and workload-simulation environments
• Conduct controlled experiments, ablation studies, sensitivity analyses, and stress tests across model families, hardware platforms, and deployment environments
• Collaborate with internal and external researchers and engineers to validate results and transfer promising technologies into HPE AI platforms
• Prepare papers and presentations for peer review, publication, and delivery at leading ML conferences and industry events

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
• Ability to implement and evaluate research ideas in Python using frameworks such as PyTorch
• 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

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