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Associate Artificial Intelligence Machine Learning Jobs in Michigan

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Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

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Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

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Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

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Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Instacart

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

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Associate Artificial Intelligence Machine Learning information

What are the key skills and qualifications needed to thrive as an Associate Artificial Intelligence Machine Learning professional, and why are they important?

To thrive as an Associate Artificial Intelligence Machine Learning professional, you need a solid background in mathematics, statistics, and computer science, typically with a relevant degree and familiarity with machine learning concepts. Proficiency in programming languages like Python or R, experience with frameworks such as TensorFlow or PyTorch, and knowledge of version control systems are commonly required. Strong problem-solving, analytical thinking, and effective communication skills help differentiate top performers in this role. These skills are crucial for developing accurate models, collaborating with multidisciplinary teams, and driving impactful AI solutions.

What is the difference between Associate Artificial Intelligence Machine Learning vs Data Scientist?

AspectAssociate Artificial Intelligence Machine LearningData Scientist
Required CredentialsBachelor's in CS, AI, or related; certifications in ML/AIBachelor's/Master's in CS, Statistics, or related; often advanced degrees
Work EnvironmentTech companies, R&D labs, startupsData-driven organizations, consulting firms, tech companies
Employer & Industry UsageAI/ML teams, product developmentData analysis, predictive modeling, business insights
Common Search & ComparisonYesYes

Associate Artificial Intelligence Machine Learning roles focus on developing and implementing AI/ML models, often with entry-level responsibilities. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require knowledge of programming and statistics, Data Scientists typically have more advanced degrees and focus on data analysis, whereas Associate AI/ML roles are more specialized in AI/ML model development.

What does an Associate Artificial Intelligence Machine Learning professional do?

An Associate Artificial Intelligence Machine Learning (AI/ML) professional assists with the development, testing, and deployment of AI and machine learning models. They typically work under the supervision of senior data scientists or machine learning engineers, helping to preprocess data, select algorithms, and evaluate model performance. Their responsibilities may also include writing code, analyzing results, and supporting the integration of models into applications or systems. This entry-level role is ideal for those who have foundational knowledge in AI/ML concepts and are looking to gain practical, hands-on experience in the field.

What are some common challenges faced by Associate Artificial Intelligence Machine Learning professionals in their first year, and how can they overcome them?

Associate AI/ML professionals often encounter challenges such as understanding complex datasets, adapting to rapidly evolving tools and frameworks, and bridging the gap between theoretical knowledge and practical application. Collaborating closely with senior team members, seeking mentorship, and participating in code reviews are effective ways to overcome these challenges. Additionally, staying updated with industry trends and continuously practicing model building on real-world problems can help associates gain confidence and accelerate their learning curve.
What are the most commonly searched types of Artificial Intelligence Machine Learning jobs in Michigan? The most popular types of Artificial Intelligence Machine Learning jobs in Michigan are:
What are popular job titles related to Associate Artificial Intelligence Machine Learning jobs in Michigan? For Associate Artificial Intelligence Machine Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Associate Artificial Intelligence Machine Learning jobs in Michigan look for? The top searched job categories for Associate Artificial Intelligence Machine Learning jobs in Michigan are:
Associate Artificial Intelligence Machine Learning jobs near you
Infographic showing various Associate Artificial Intelligence Machine Learning job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Data Scientist (ARTIFICIAL INTELLIGENCE/MACHINE LEARNING)

Defense Logistics Agency

Battle Creek, MI

Full-time

Posted yesterday

New

Defense Logistics Agency rating

8.3

Company rating: 8.3 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

274th of 842 rated public administrative organizations

Job description

Telework Eligible

Yes

Major Duties

  • Serves as an Al (Artificial Intelligence) Testing and Evaluation Data Scientist providing subject matter Al expertise and execution to test and evaluate Al systems.
  • Provides professional and scientific expertise in the application of data science disciplines for complex studies in machine learning and deep learning algorithms, statistical analysis, visualizations, programing and computer science.
  • Provides expertise in evaluating and measuring data science and artificial intelligence systems in accordance with data science Lifecyle practices within DoD parameters.
  • Ensures Al systems are developed in accordance with applicable legal frameworks such as General Data Protection Regulation (GDPR) and National Institute of Standards and Technology (NIST).
  • Incorporates, Office of Management and Budget (0MB) test and evaluation requirements, DOD Al ethical principles into DLA Al test and evaluation framework to generate an RAI test strategy for modeling cases.
  • Utilizes expertise to coordinate the integration of the DLA Al testing and evaluation program during the product lifecycle from concept and design inception, as development proceeds, and integrated to ensure effective RAI implementation.

Qualification Summary

To qualify for a Data Scientist (Artificial Intelligence/Machine Learning), your resume and supporting documentation must support: A. Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position. B. Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position. To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-after­competitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes: Conducts large, agency wide, research and development reviews of metrics, measurements, and evaluation methods for emerging and existing areas of Al. Utilizes data science expertise to develop algorithms and tools to support data manipulation and processing as well as the use of data visualization techniques to articulate high risk findings. Ensures the Al systems are designed for auditability to manage Al risk assessment policies and principles which guide automated decisions supporting DLA business operations. Provides expert advice to senior leadership and Al stakeholders to adopt new or revised policy and implementation plans resulting from Al test and evaluation integration. Assesses data quality and establishes standards to validate quality criteria for data to ensure it meets the necessary requirements for Al testing and evaluation. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

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