Applied Math Research Jobs in Michigan (NOW HIRING)

Sub Department: Michigan Tech Research Institute department Michigan Technological University is an R1 technological research university founded in 1885 in Houghton. Our rural campus is situated just miles from Lake Superior in Michigan's scenic Upper Peninsula and is home to nearly 7,500 students from more than 60 countries around the world. Consistently ranked among the best universities in the country for return on investment, Michigan's flagship technological university offers more than 185 undergraduate and graduate degree programs. Research focus areas include defense, health, energy, automotive, environment, and aerospace. The area's waters, forests, and snowfall support year-round recreation, including skiing, snowboarding, hiking, biking, and paddling. The University is an integral part of the region, supported by a friendly and welcoming community that takes pride in being a true college town. We embrace our size, climate, sense of adventure, and originality. Summary Michigan Technological University is seeking a Machine Learning Engineer II for out Michigan Tech Research Institute department. At MTRI, we develop advanced technologies that help our nation better understand, sense, and operate within complex natural and human-made environments. Our work spans multidisciplinary research and applied development, advancing ideas from foundational concepts to mission-relevant prototypes. We are seeking a Machine Learning (ML) Engineer to contribute to applied ML research and development efforts in a government-focused research and development (R&D) environment. This role focuses on developing, implementing, and evaluating ML algorithms and systems, supporting the advancement of capabilities from early-stage concepts to prototype demonstrations. The successful candidate will contribute to research programs while developing increasing independence in technical problem-solving and solution development. Candidates for this position may opt to work in either Ann Arbor, MI or Dayton, OH Responsibilities and Essential Duties 1. Develop and evaluate ML algorithms for mission-relevant applications 2. Support advancement of ML capabilities from applied research concepts to working prototype demonstration 3. Design, implement, and evaluate ML models for structured, unstructured, or sensor-derived data 4. Develop data processing pipelines, feature extraction workflows, and training/evaluation frameworks 5. Apply sound experimental methodologies to assess model performance and robustness 6. Work with cross-functional teams (software, sensing, systems engineering) to develop prototype ML systems 7. Contribute to technical documentation, reports, and proposal development activities 8. Commit to learning about continuous improvement strategies and applying them to everyday work. Actively engage in University continuous improvement initiatives 9. Apply safety-related knowledge, skills, and practices to everyday work. Required Education, Certifications, Licensures • Bachelor's degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or related technical field Required Experience • Minimum of 3 years of relevant experience with Bachelor's degree, OR minimum of 1 year of relevant experience with a Master's degree Desirable Education and/or Experience 1. Master's degree in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or related technical field 2. 4-10 years of experience in a related technical field
3. Experience with remote sensing, RF data, or sensor-derived datasets 4. Experience with MLOps, CI/CD, or model lifecycle management 5. Familiarity with cloud or on-prem compute environments 6. Experience with distributed computing or GPU acceleration Required Knowledge, Skills, and/or Abilities 1. Ability to obtain a U.S. Department of Defense (DoD) security clearance, which requires United States citizenship. Obtaining a national security clearance while holding a dual citizenship will not be possible when the foreign country poses a risk to the national security of the United States. 2. Experience developing ML models and working with modern ML frameworks (e.g., PyTorch, TensorFlow) 3. Proficiency in Python and scientific computing libraries 4. Experience with data processing, model evaluation, and experimental design 5. Ability to design, implement, and evaluate ML models for structured, unstructured, or sensor-derived data 6. Familiarity with software development practices and version control 7. Ability to work collaboratively in a multidisciplinary research environment. 8. Strong written and verbal communication skills. Desirable Knowledge, Skills, and/or Abilities 1. Active government security clearance at Secret-level or higher 2. Exposure to DoD or DARPA-funded research environments 3. Ability to lead the execution of well-defined technical tasks, including planning, implementation, and reporting 4. Ability to provide technical input to proposal sections, including methods, data approaches, or evaluation strategies 5. Ability to serve as a technical resource to junior staff or team members in a limited domain Work Environment and/or Physical Demands WORK ENVIRONMENT: The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The noise level in the work environment is usually low to moderate. Required Training and Other Conditions of Employment Every employee at Michigan Technological University will receive the following 4 required trainings; additional training may be required by the department. Required University Training:
• Employee Safety Overview
• Anti-Harassment, Discrimination, Retaliation Training
• Annual Data Security Training
• Annual Title IX Training Additional training will be required by the department on a periodic basis. Background Check:
Offers of employment are contingent upon and not considered finalized until the required background check has been performed and the results received and assessed.