About the job
About Us
Who We're Seeking
As a Principal Machine Learning Engineer within our Delivery team, you will be an accomplished problem solver and technical strategist focused on delivering impactful solutions. You possess the ability to comprehend sophisticated engineering principles across diverse industries, spearhead technical projects, and collaborate closely with customers, often working alongside them on-site to integrate cutting-edge AI models into practical and effective tools.
You have successfully deployed ML systems end-to-end at scale: designing, constructing, and validating reliable, scalable ML data pipelines. You are proficient in exploring and manipulating 3D point-clouds and mesh data to facilitate geometry-aware modeling. Your expertise includes selecting the most suitable libraries, frameworks, and tools, enabling you to make pragmatic product choices that set the Delivery team up for success. At the intersection of data science and software engineering, you translate R&D findings and project outcomes into reusable libraries, tools, and products.
With a minimum of 3 years of industry experience (post-Master's or PhD) in a commercial setting (not research-focused), you are poised to not only execute but also lead and mentor your peers. You are genuinely enthusiastic about taking ownership of complex projects and guiding teams toward success while continuously enhancing the systems and solutions you work on to ensure they remain practical, impactful, and aligned with our customers' evolving needs.
This Role
In the role of Principal Machine Learning Engineer, you will work collaboratively with our Data Scientists, Simulation Engineers, and customers to identify and articulate the engineering and physics challenges we aim to address. You will iterate with clients and leverage your influence to drive decisions regarding reliable deployments that yield measurable outcomes.
Your responsibilities will include:
- Leading the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization & control) into customer production environments.
- Effectively communicating results and technical insights to stakeholders, ensuring alignment and understanding.

