# Machine Learning Post Doctoral Research Scientist

**Company**: Hewlett Packard Enterprise
**Location**: Milpitas, California
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Salary**: Annual Salary USD 99,320 - 149,760
**Category**: Research
**Industry**: Technology

**Apply**: https://hpe.wd5.myworkdayjobs.com/en-US/Jobsathpe/job/Milpitas-California-United-States-of-America/Machine-Learning-Post-Doctoral-Research-Scientist_1215883?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_d2e68201-052

## Description

This Post Doctoral Research Scientist role sits within the core Machine Learning research team at Hewlett Packard Labs, HPE's primary research organization, based in the San Francisco Bay Area.

You will bridge frontier research with real-world impact, tackling complex challenges such as nuclear fusion, supercomputing and data center sustainability, quantum computing acceleration, and the trustworthiness of AI/LLM-based systems.

Responsibilities:

- Conduct original research and develop novel technologies across areas, including LLM reasoning, agentic and multi-agent systems, reinforcement learning, generative modeling, digital twins, clean energy, and data center/private cloud optimization.

- Provide technical thought leadership, collaborate closely with internal teams and external partners, and contribute to HPE's research and product strategy by identifying and shaping emerging technology opportunities.

- Publish at leading venues (e.g., NeurIPS, ICML, AAAI) and develop patent disclosures.

- Software prototyping and engineering, GPU acceleration, model optimization, and real-time data/streaming workflows to deliver robust AI capabilities for production-relevant use cases.

Qualifications and Education Requirements:

- PhD in Computer Science, Electrical Engineering, or related fields, focusing on Machine Learning for the dissertation.

- Extensive experience with emerging Machine Learning techniques like diffusion models, LLMs, multi-agent systems, and Reinforcement Learning.

- Experience in developing applications with deep learning frameworks like PyTorch, with a high level of software proficiency.

Preferred Skills:

- Experience in applying ML to nuclear fusion.

- Experience with Generative models.

- Experience and deep knowledge of different deep learning model architectures, uncertainty quantification, optimization, control, digital twins, and world models.

- Strong programming skills in Python, data structures, and algorithms are required.

- Experience with ML model optimization, GPU acceleration, heterogeneous computation, system software, and performance optimization is desired.

Benefits:

- Comprehensive suite of benefits that supports physical, financial, and emotional wellbeing.

- Investment in career development.

- Unconditional inclusion and flexibility to manage work and personal needs.

## Skills

### Required
- Machine Learning
- Python
- PyTorch
- Reinforcement Learning
- Generative models
- Deep Learning

### Nice to have
- Nuclear Fusion
- Digital Twins
- Optimization
- GPU Acceleration

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