DISA Technologies is revolutionizing mineral recovery with their patented High-Pressure Slurry Ablation (HPSA) technology. The Machine Learning Engineer will design, build, and deploy machine learning models that support DISA’s mineral recovery and remediation operations, enhancing operational performance and efficiency.
Requirements
- Proficiency in programming languages, including Python, and machine learning libraries (PyTorch, TensorFlow, scikit-learn).
- Strong foundation in statistics, data modeling, and numerical methods.
- Experience with applied machine learning in real-world data contexts.
- Familiarity with data engineering tools and workflows (SQL, data pipelines, APIs).
- Ability to analyze large, complex data sets and extract actionable insights.
- Apply strong analytical and problem-solving skills to manage multiple projects effectively.
- Experience applying statistical, numerical, or AI methods to real-world problems.
Responsibilities
- Develop, train, and deploy machine learning models for HPSA process optimization and predictive analytics.
- Review and refine HPSA ML models.
- Apply numerical methods, statistical learning, and data-driven modeling to improve system monitoring and control.
- Contribute to generative modeling and data analysis projects to accelerate materials and process discovery.
- Implement shape- and geometry-based statistical tools for manufacturing process monitoring.
- Support the integration of machine learning pipelines into production systems.
- Document methods, maintain codebases, and ensure reproducibility of results.
Other
- Assist engineers in determining HPSA systems where ML could benefit the operation.
- Collaborate with all internal disciplines, and manage external partners, as necessary, on projects.
- Abide by all policies and procedures established by DISA.
- Attend and participate in all required safety trainings.
- Assist with any task required by the direct supervisor.
