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Internship Machine Learning Hardware Jobs in Michigan

Familiarity with robotics frameworks (ROS 2) and machine learning is a plus. Key Responsibilities ... Collaborate with hardware engineers on PCB, power, and signal design to ensure seamless system ...

Familiarity with robotics frameworks (ROS 2) and machine learning is a plus. Key Responsibilities ... Collaborate with hardware engineers on PCB, power, and signal design to ensure seamless system ...

You will develop the "connective tissue" between high-performance machine learning models running on edge hardware and our Google Cloud-based analytics backend. This is a hands-on role for an ...

We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery ... Train new machine learning models to solve complex business problems. * Prototype new AI solutions ...

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

... hardware, aftermarket connectivity, and AI-driven security solutions. As part of our team, you'll ... Lead the design, development, and implementation of advanced machine learning models and algorithms ...

Full Year Intern-IT

Detroit, MI · On-site

$14.75 - $19.75/hr

Knowledge of deep learning, machine learning, and neural networks. * Working knowledge of Python, SQL, and Power BI. The Internship Program at BCBSM is designed to enhance the skills and abilities of ...

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Internship Machine Learning Hardware information

What is the difference between Internship Machine Learning Hardware vs Internship Data Scientist?

AspectInternship Machine Learning HardwareInternship Data Scientist
Required CredentialsBasic knowledge of hardware, electronics, and programmingStatistics, programming, and data analysis skills
Work EnvironmentHardware labs, electronics workshops, manufacturing settingsOffice, data analysis environments, cloud platforms
Employer & Industry UsageTech companies, hardware manufacturers, research labsTech firms, finance, healthcare, consulting
Common Search & Comparison IntentUnderstanding hardware-focused roles in ML projectsData analysis and modeling roles in ML

Internship Machine Learning Hardware focuses on developing and optimizing hardware components for ML systems, while Internship Data Scientist emphasizes analyzing data and building models. Both roles are essential in AI development but differ in skills, environment, and industry application.

What is an Internship in Machine Learning Hardware?

An Internship in Machine Learning Hardware is a temporary position for students or recent graduates to gain hands-on experience working with the physical components and systems that enable machine learning applications. Interns typically assist in designing, testing, and optimizing hardware such as GPUs, TPUs, or custom accelerators that run machine learning algorithms efficiently. This role often involves collaboration with software engineers and researchers to improve the performance and energy efficiency of machine learning models. The internship provides valuable exposure to both hardware engineering and the rapidly evolving field of artificial intelligence.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Hardware, and why are they important?

To thrive as an Internship Machine Learning Hardware, you need a solid foundation in computer engineering, electrical engineering, or computer science, with coursework or experience in machine learning and hardware design. Familiarity with hardware description languages (like Verilog or VHDL), Python, C++, and tools such as TensorFlow, PyTorch, or FPGA development environments is typically required. Strong problem-solving abilities, eagerness to learn, and effective teamwork and communication skills help interns excel in multidisciplinary environments. These competencies are crucial for contributing to hardware-accelerated machine learning solutions and collaborating efficiently with engineering teams.

What kinds of projects and responsibilities can I expect during an Internship in Machine Learning Hardware?

As an intern in Machine Learning Hardware, you can expect to work on tasks such as benchmarking hardware performance for AI workloads, supporting the development and testing of new accelerator architectures, and optimizing hardware-software integration for machine learning models. You'll often collaborate with both hardware engineers and machine learning researchers, gaining exposure to the entire workflow from design to deployment. These internships typically provide hands-on experience with tools like FPGA, ASIC simulation environments, or specialized ML hardware platforms, and offer opportunities to contribute to real-world product development and research.
What are popular job titles related to Internship Machine Learning Hardware jobs in Michigan? For Internship Machine Learning Hardware jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Internship Machine Learning Hardware jobs in Michigan look for? The top searched job categories for Internship Machine Learning Hardware jobs in Michigan are:
What cities in Michigan are hiring for Internship Machine Learning Hardware jobs? Cities in Michigan with the most Internship Machine Learning Hardware job openings:
Machine Learning Program Lead with Security Clearance

Machine Learning Program Lead with Security Clearance

Michigan Technological University

Ann Arbor, MI • On-site

Other

Posted 8 days ago


Michigan Technological University rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

134th of 553 rated colleges and universities


Job description

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 serving as Principal Investigator on multiple funded research programs 3. Experience managing technical execution across multiple concurrent programs 4. Experience advancing technologies across TRLs, particularly from TRL 2-3 through TRL 5-6 5. Experience mentoring or supervising technical staff Desirable Education and/or Experience 1. Experience in mission-relevant domains such as remote sensing, RF sensing, geospatial analytics, or multimodal sensor fusion 2. Experience integrating ML capabilities into sensing systems or hardware platforms
3. Experience designing scalable compute architectures (cloud, hybrid, or on-prem) 4. Experience establishing MLOps or DevOps practices in research or secure environments 5. Experience implementing cybersecurity considerations for AI systems Required Knowledge, Skills, and/or Abilities 1. Ability to obtain a U.S. Department of Defense 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. Proven track record of leading and winning competitive government research proposals 3. Demonstrated technical authority in AI/ML research or applied ML system development 4. Strong programming proficiency in Python and experience with modern AI/ML frameworks 5. Exceptional written and verbal communication skills, including experience briefing sponsors and senior leadership Desirable Knowledge, Skills, and/or Abilities 1. Familiarity with high-performance computing (HPC) or GPU-based architectures 2. Active U.S. Department of Defense security clearance at Secret-level or higher 3. Demonstrated success in, or potential future contributions to, working with persons with a wide variety of backgrounds and viewpoints 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. Please note that successful applicants must have the ability to obtain a U.S. Department of Defense 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.

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