AI Research Scientist

Austin Powder•Beachwood, OH

About The Position

Join the Family - Come work for an exciting company offering great benefits, challenging opportunities, and colleagues who feel more like family. Austin Powder has been making explosives for over 190 years and we take great pride in improving the world we live in. In 1833, the Austin family created the company to produce black powder that would help break the rock, mine the minerals and build the canals and railroads to develop the frontier. Initially along the banks of the Cuyahoga River near Akron, Ohio, we grew as the country grew. Today, Austin Powder is a world leader in the industrial explosives industry with a passionate commitment towards safety, a relentless customer focus, a family culture work environment, and a demonstration of respect of towards all. As in our early years, our mission continues to be to improve the world we live in through the safe and responsible use of explosives. Our success has been based on our core values and this has proven to be universally true around the globe as the company has expanded to be one of the leading providers of industrial explosives and blasting services in the world.

Requirements

PhD or Master's degree in Artificial Intelligence, Machine Learning, Computer Science, Mining Engineering, Geomechanics, or a closely related discipline.
Minimum 5 years of post-doctoral or industry research experience applying AI/ML to engineering or industrial process domains.
Demonstrated track record of delivering production-grade AI models in live operational environments.
Proficiency in Python (PyTorch / TensorFlow / JAX, scikit-learn, NumPy/SciPy) and SQL-based data environments.
Experience with ML pipelines, experiment tracking (MLflow / W&B), model versioning, and CI/CD for ML in production.
Knowledge of physics-informed neural networks (PINNs), surrogate modelling, or digital twins in engineering contexts.
Working knowledge of explosives technology principles including detonation physics, initiation systems, and bench blasting design.
Strong communication skills with the ability to translate complex AI outputs for non-technical stakeholders.

Nice To Haves

Direct experience working on mine sites or within an explosives manufacturing or services environment is highly desirable.
Strong publication record or portfolio of applied research deliverables demonstrating scientific rigor and practical impact.
Familiarity with geomechanics software such as Leapfrog, Vulcan, Datamine, or WipFrag is an advantage.

Responsibilities

Design and validate ML models for blast fragmentation prediction, muckpile movement, flyrock risk assessment, flyrock tracking, terrain building and identification models for blast holes, stockpiles and equipment.
Develop AI-driven blast design tools that integrate geotechnical surveys, rock mass classifications, and explosives product parameters.
Build predictive maintenance models based on fleet utilization, pump/auger usage, etc.
Create NLP and computer-vision tools to automate compliance auditing against based on MSHA regulations.
Develop real-time air blast, ground vibration, and muckpile prediction models linked to live sensor networks.
Publish research findings in peer-reviewed journals and present at industry conferences (EFEE, ISEE, etc.).
Mentor junior data scientists and collaborate with OEM partners and university research programs.