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Scientific Machine Learning Jobs in Michigan (NOW HIRING)

Senior Machine Learning Engineer

Warren, MI · On-site +1

$222.91K - $227.20K/yr

Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics Engineering or a related field and Two (2) years of experience as a Software Engineer, Machine Learning ...

AI and Machine Learning Engineer

Detroit, MI · On-site

$104.80K - $125.80K/yr

Machine Learning And Artificial Intelligence Developer You will be responsible for Machine Learning ... Bachelors, Masters in Computer Science/ Computer Engineering/ Information Systems/Information ...

... machine learning models to address specific business needs (e.g., prediction, classification ... data science, machine learning, and relevant technologies. Skills Required: • Demonstrated ...

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Scientific Machine Learning information

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Michigan? For Scientific Machine Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Michigan look for? The top searched job categories for Scientific Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Scientific Machine Learning jobs? Cities in Michigan with the most Scientific Machine Learning job openings:
Machine Learning Engineer II

Machine Learning Engineer II

Michigan Technological University

Ann Arbor, MI • On-site

Full-time

Posted 23 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

128th of 528 rated colleges and universities


Job description

Machine Learning Engineer II
Job No: 26057
Department: Michigan Tech Rsrch Institute(MTRI)
Work Type: Staff - Full Time
Location: Michigan Tech Research Institute (Ann Arbor, MI)
Full Time / Part Time: Full Time
Categories: Research
Applications Close:
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.
Full-Time Equivalent (FTE) % (1=100%)
1
FLSA Status
Exempt
Appointment Term
12 months
Shift
Pay Rate/Salary
Salary is commensurate with experience and qualifications.
Title of Position Supervisor
Research Engineer III
Posting Type
Internal & External Posting
Dependent on Funding
Yes
Additional Information
This position is contingent upon the continued availability of external funding.
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
If you require any auxiliary aids, services, or accommodations during Michigan Tech's hiring process please notify the Human Resources office at 906-487-2280 or hr-help@mtu.edu.
Other Conditions of Employment:
Please note that successful applicants are responsible for ensuring their eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of your appointment, and maintain eligibility without sponsorship throughout your appointment.
Michigan Technological University is an Equal Opportunity Educational Institution/Equal Opportunity Employer that provides equal opportunity for all, including protected veterans and individuals with disabilities.
The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. Michigan Tech will provide a paper copy upon request; please contact the Michigan Tech Public Safety.
In compliance with the federal Drug-Free Schools and Communities Act (DFSCA) and its implementing regulations (34 CFR Part 86), Michigan Tech is committed to maintaining a drugfree campus environment and actively promoting the health and safety of its community. Find our notice that outlines the University's policies, legal sanctions, health risks, and available support resources related to the unlawful possession, use, or distribution of illicit drugs and alcohol.
Required Education, Certifications, Licensures* (minimum requirements)
Advertised: 05 May 2026 Eastern Daylight Time
Applications Close:
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