Machine Learning Program Lead

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

At Michigan Tech Research Institute (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 senior technical leader to build, grow, and direct MTRI’s machine learning (ML) research portfolio within a government-focused R&D environment. This role will shape our ML strategy, lead business development efforts, and serve as Principal Investigator on multiple programs. This position operates at the intersection of research leadership, program execution, and institutional growth. It is not a pure software engineering role.

This role is responsible for:

• Leading development and execution of MTRI’s ML portfolio and growth strategy aligned with sponsor priorities
• Leading capture efforts and grow a portfolio of funded ML programs
• Serving as Principal Investigator on multiple programs
• Advancing ML capabilities from early-stage concepts (TRL 1–3) to prototype demonstrations (TRL 4–6)
• Establishing internal ML technical standards and mentoring technical staff • Providing technical direction and mentorship across ML-related efforts.

Responsibilities and Essential Duties

1. Define and maintain a multi-year ML research and growth roadmap aligned with sponsor priorities (DoD, AFRL, DARPA, etc.).
2. Identify emerging ML opportunities and shape them into competitive program concepts.
3. Develop and manage a portfolio of ML-focused research programs.
4. Contribute to institutional planning related to AI/ML capability development.
5. Lead and author technical volumes for white papers, BAAs, SBIR/STTR submissions, and other competitive proposals. 6. Demonstrate ownership of proposal strategy, technical approach, and win themes.
7. Identify and pursue new business opportunities aligned with emerging sponsor demand signals.
8. Build and maintain sponsor relationships to position MTRI for future work.
9. Develop teaming strategies and external partnerships to support transition beyond TRL 4.
10. Serve as Principal Investigator on multiple funded programs.
11. Provide overarching technical direction across ML efforts.
12. Ensure technical execution aligns with scope, budget, schedule, and performance metrics.
13. Establish rigorous experimental design, validation, and evaluation standards.
14. Oversee advancement of ML technologies from concept through prototype validation.
15. Serve as a technical authority in AI/ML within the Institute.
16. Mentor junior technical staff and guide cross-disciplinary integration across sensing, analytics, and systems teams. 17. Establish technical standards for ML reproducibility, data governance, and secure AI implementation.
18. Evaluate emerging AI hardware and software frameworks and guide adoption decisions.
19. Commit to learning about continuous improvement strategies and applying them to everyday work. Actively engage in University continuous improvement initiatives.
20. Apply safety-related knowledge, skills, and practices to everyday work.

Required Education, Certifications, Licensures

PhD in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or closely related technical field

Required Experience

1. 12–18 years of experience in applied research and development environments
2. Demonstrated experience serv