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Junior Machine Learning Jobs in Michigan (NOW HIRING)

Corning

$95K - $130K/yr

... junior contributors, lead code reviews and technical documentation, and partner with data ... in machine learning engineering, data engineering, software engineering, or a related technical ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director ... In this senior role, you'll play a pivotal part in shaping our AI roadmap, mentoring junior ...

Deloitte

Lead AI and Data Science Engineer II

Detroit, MI · On-site

$101K - $133K/yr

Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing ... Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ...

Deloitte

Lead AI and Data Science Engineer II

Midland, MI · On-site

$88K - $115K/yr

Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing ... Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ...

Deloitte

Lead AI and Data Science Engineer II

Grand Rapids, MI · On-site

$98K - $129K/yr

Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing ... Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns ...

Deloitte

Senior AI Engineer - SFL Scientific

Detroit, MI

$103K - $142K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

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Junior Machine Learning information

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Michigan?

The most popular types of Machine Learning jobs in Michigan are:

What are popular job titles related to Junior Machine Learning jobs in Michigan?

For Junior Machine Learning jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning jobs in Michigan look for?

The top searched job categories for Junior Machine Learning jobs in Michigan are:

What cities in Michigan are hiring for Junior Machine Learning jobs?

Cities in Michigan with the most Junior Machine Learning job openings:

Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Sr. Machine Learning Engineer

Corning

$95K - $130K/yr

Full-time

Re-posted 8 days ago

Corning rating

8.2

Company rating: 8.2 out of 10

Based on 128 frontline employees who took The Breakroom Quiz

89th of 540 rated manufacturers

Job description

Are you ready to lead the technical delivery of production-grade machine learning solutions that can transform manufacturing performance?

What is your role?

As a Senior Machine Learning Engineer, you will design, deploy, maintain, and improve robust machine learning systems that support manufacturing and other business functions. You will help translate data science prototypes into secure, scalable, and production-ready solutions while influencing architecture, MLOps practices, and technical standards. This is an individual contributor role based in Monterrey with regular onsite presence and hybrid flexibility.

Major responsibilities and tasks of the position:-

Design, build, and maintain end-to-end machine learning pipelines covering data ingestion, preprocessing, training, validation, deployment, model serving, monitoring, troubleshooting, and retraining.-

Lead the translation of prototypes into scalable production solutions and contribute to architecture and technology decisions for APIs, batch processing, and real-time systems.- Implement MLOps and DevOps practices for model versioning, orchestration, CI/CD, containerization, security, data privacy, and production reliability.

- Guide junior contributors, lead code reviews and technical documentation, and partner with data scientists, IT, analytics, and manufacturing stakeholders to resolve complex production issues.

What do you need to have?

- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Software Engineering, Data Engineering, or a related technical field.- At least 3 years of relevant experience in machine learning engineering, data engineering, software engineering, or a related technical role; 3-5 years is preferred.- Proven hands-on experience deploying and supporting machine learning models or systems in production environments.

- Strong Python proficiency and experience with machine learning frameworks or libraries such as scikit-learn, TensorFlow, or PyTorch.- Hands-on understanding of the end-to-end ML lifecycle and MLOps/DevOps concepts, including CI/CD, model versioning, orchestration, monitoring, and containerization.

- Ability to influence architecture and design decisions, troubleshoot complex production issues, and coach or guide less-experienced team members without direct reports.

- Advanced technical and business English, plus the ability to work onsite in Monterrey at least two days per week and support plant-based projects as needed.

What would be a plus?

- Experience with Databricks, MLflow, Kubeflow, Docker, Kubernetes, cloud or on-premise deployment, and enterprise systems integration.- Experience deploying ML solutions in manufacturing, industrial, quality, defect-reduction, or production-optimization environments.- Experience with APIs, model serving infrastructure, relational or non-relational databases, distributed computing, security, and data privacy.

What do we offer?

- Competitive benefits above the requirements of Mexican law.

- Opportunity to work on high-impact machine learning initiatives that support manufacturing and business transformation.

- Collaborative global environment with exposure to Data Science, IT, analytics, and manufacturing teams.

- Learning and career development in a growing technical organization.Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodation to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodations related to disability or religion, please contact us at accommodations@corning.com 

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