Machine Learning Engineer at DISA Technologies

Casper, Wyoming, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Jan, 26

Salary

0.0

Posted On

18 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Analysis, Statistical Analysis, Numerical Modeling, Python, PyTorch, TensorFlow, Scikit-learn, SQL, Data Pipelines, APIs, Analytical Skills, Problem-Solving, Collaboration, Communication, Attention To Detail

Industry

Description

About Us Are you ready to be part of a team that is bringing revolutionary technology to the remediation industries? DISA Technologies is revolutionizing mineral recovery with our patented High-Pressure Slurry Ablation (HPSA) technology—an innovative solution that upgrades critical minerals from mined ore and legacy waste. Serving both the mining and remediation sectors, we recover valuable resources that power industry, strengthen energy independence, and restore contaminated sites to productive use. Our technology unlocks economic and environmental value, transforming how the world processes, remediates, and recycles essential mineral assets. Job Summary The Machine Learning Engineer will design, build, and deploy machine learning models that support DISA’s mineral recovery and remediation operations. This role focuses on applying modern AI/ML methods, numerical modeling, and statistical analysis to complex industrial data. The successful candidate will work closely with cross-functional teams to deliver practical, data-driven solutions that enhance operational performance and efficiency. The ideal candidate will have experience in machine learning, applied mathematics, and data analysis, with the ability to translate advanced concepts into working solutions in a fast-paced environment. Education/ Experience Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field. 3–5 years of experience in machine learning, applied data science, or computational modeling. Experience applying statistical, numerical, or AI methods to real-world problems. Industry experience in chemicals, energy, materials, or industrial systems preferred. Supervisor Senior Process Engineer, unless otherwise designated. Typical Job Duties and Responsibilities Assist engineers in determining HPSA systems where ML could benefit the operation. 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. Collaborate with all internal disciplines, and manage external partners, as necessary, on projects. 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. 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. Required Skills 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. Communicate clearly and professionally, both verbally and in writing, to collaborate with colleagues, stakeholders, and clients. Organize and prioritize tasks to meet deadlines while managing multiple projects. Collaborate effectively as part of a team, supporting shared goals and fostering positive relationships. Adapt to dynamic environments and identify solutions to challenges with flexibility and problem-solving skills. Maintain professionalism with high attention to detail, reliability, accountability, and accuracy in all work deliverables. Uphold and demonstrate DISA’s Values of Dedication, Innovation, Sustainability, and Accelerate Change. Ability to follow safety protocols and maintain compliance with OSHA/MSHA and company safety standards. Be a valid U.S. citizen or legally authorized to work in the United States. Possess a valid driver’s license with a clean driving record. Physical Requirements Must be able to sit and/ or stand for extended periods of time. Must be able to lift up to 25 lbs. occasionally. Must be able to interact with people and technology while either standing or sitting. To best service our customers, all employees must be able to communicate face-to-face and on the phone with or without reasonable accommodation. Ability to travel up to 50%. Must be able to perform repetitive tasks such as typing. DISA Technologies provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. Bonus Pool 401(k) with matching up to 4% Employee stock options Health insurance Dental insurance Vision insurance Life insurance Paid holidays Paid time off Professional Development

Responsibilities

The Machine Learning Engineer will design, build, and deploy machine learning models to support mineral recovery and remediation operations. This role involves applying AI/ML methods and statistical analysis to complex industrial data.