AI and Machine Learning Engineer III (LLM)

Location: Hybrid in Milpitas, California, United States; average of 2 days per week in an HPE office required

Base salary: USD 143,000–290,500 annually in California; variable incentives may also be offered.

Company

hirify.global is a global edge-to-cloud company developing technologies that connect, protect, analyze, and act on data and applications.

What you will do

• Investigate, design, develop, and implement AI tokenomics research for new products, technologies, and intellectual property.
• Research and prototype representations of jobs and system states and predict workload complexity, answer quality, latency, token demand, energy, and cost.
• Develop routing policies, model cascades, and adaptive controllers for selecting LLMs, reasoning modes, retrieval strategies, tool chains, and deployment targets across local, edge, private-cloud, and public-cloud environments.
• Develop methods for assigning and enforcing token, context, reasoning, and compute budgets based on job difficulty, priority, risk, service-level objectives, and business value.
• Build benchmark, telemetry, accounting, and workload-simulation environments; conduct controlled experiments, ablation studies, sensitivity analyses, and stress tests.
• Collaborate with researchers and engineers, transfer promising technologies into HPE AI platforms, and prepare papers, presentations, patent disclosures, and supporting documentation.

Requirements

• Completed or soon-to-be-completed PhD 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.
• 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.
• Experience applying 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, including the ability to communicate research plans, proposals, and results and negotiate options at management levels.

Nice to have

• 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.

Culture & Benefits

• Health, financial, and emotional wellbeing benefits are offered to US employees and their loved ones.
• Professional development programs support career growth and movement across areas of the organization.
• Inclusive workplace with flexibility to manage work and personal needs.
• HPE is committed to accessibility and can provide reasonable accommodation during the application or interview process.