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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 ...

Canopy

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

Lead the design, development, and implementation of advanced machine learning models and algorithms ... Mentor and provide guidance to junior data scientists and analysts, fostering a culture of ...

Apex Systems

ML Ops Engineer

Dearborn, MI · On-site

$48.50 - $66.50/hr

Key Responsibilities ML Ops & Machine Learning * Build scalable, secure, and high-performance ML ... Mentor junior team members and promote best practices across the team Required Skills * Strong ...

Pwc

ERP AI Engineer - Senior Associate

Detroit, MI

$77K - $202K/yr

Responsibilities - Design and implement advanced AI and machine learning solutions - Analyze intricate challenges and provide actionable insights - Mentor and guide junior team members in their ...

Pwc

ERP AI Engineer - Senior Associate

Grand Rapids, MI

$77K - $202K/yr

Responsibilities - Design and implement advanced AI and machine learning solutions - Analyze intricate challenges and provide actionable insights - Mentor and guide junior team members in their ...

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Junior Machine Learning information

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 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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise with tools like TensorFlow or PyTorch, and may require multiple years of experience and relevant certifications.

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 engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of specialized experience and a strong track record of impactful projects.

Can I get an AI job with no experience?

Entry-level machine learning roles, such as Junior Machine Learning positions, often require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is beneficial, candidates can improve their chances by completing relevant online courses, building projects, and gaining familiarity with tools like Python and TensorFlow.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and machine learning engineers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

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

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 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 July 2026, with employment types broken down into 89% Full Time, 7% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.
Sr. Machine Learning Engineer

Sr. Machine Learning Engineer

Corning

On-site

$95K - $130K/yr

Full-time

Posted 17 days ago

Corning rating

8.2

Company rating: 8.2 out of 10

Based on 128 frontline employees who took The Breakroom Quiz

86th of 535 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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