Principal Research Scientist - Frontier Industrial AI

We are looking for exceptional researchers who combine original thinking with the ability to turn ambitious ideas into working systems.

You will define and pursue high-impact research questions, build experimental prototypes, publish influential work, and create defensible intellectual property. Research may span industrial foundation models for time-series and multimodal data, simulation and world models, trustworthy decision-support agents and staged autonomy, and AI-native approaches to industrial data foundations, ontology learning, and evaluation.

This is a hands-on role for someone who thrives in uncertain problem spaces, works with high autonomy, and finds practical ways to move difficult initiatives forward.

- Define and lead ambitious research initiatives in frontier industrial AI.

- Develop new models, algorithms, evaluation methods, and system architectures.

- Build high-quality experimental systems and validated research prototypes.

- Publish at leading AI and machine learning venues and contribute to AVEVA's patent and IP portfolio.

- Create benchmarks, datasets, and evaluation frameworks for industrial AI.

- Partner with leading AI labs, universities, and technology organizations

- Take research from initial hypothesis through prototype and validation

- Help shape AVEVA's longer-term AI research direction and technical strategy.

- A PhD or equivalent research experience in machine learning, artificial intelligence, computer science, applied mathematics, engineering, or a related field.

- Evidence of original research through strong publications, patents, open-source work, prototypes, or other meaningful technical contributions.

- Strong hands-on ability in AI experimentation and software development.

- Ability to independently identify important problems, formulate research hypotheses, and execute projects with limited structure.

- Deep expertise in one or more areas such as foundation models, multimodal learning, time-series modeling, generative models, reinforcement learning, agentic systems, simulation, world models, representation learning, or AI evaluation.

- Strong scientific judgment and the ability to design rigorous experiments and communicate results clearly.

- High agency, intellectual curiosity, and a constructive problem-solving mindset.

- Ability to collaborate across research, engineering, product, and teams.

- Experience working with industrial, manufacturing, energy, infrastructure, engineering, or scientific data.

- Recent publications at leading machine learning, AI, data mining, robotics, or systems venues.

- Experience developing models at scale or building complex research systems.

- Experience with simulation environments, digital twins, multimodal data, or industrial time series.

- A track record of initiating and advancing research projects with limited supervision.

- Exceptional recent PhD graduates with a strong research record are encouraged to apply.