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Junior Machine Learning Engineer Jobs in Michigan

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Stefanini is looking for a Machine Learning Engineer, Dearborn, MI (Onsite) For quick apply, please reach out Saurabh Kapoor at / You will be responsible for designing, building, deploying, and ...

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 ...

Machine Learning Engineer

Dearborn, MI

$105.50K - $126.60K/yr

Stefanini is looking for a Machine Learning Engineer (Dearborn, MI) For quick apply, please reach ... Ability to mentor and advise junior team members Education RequiredBachelor's Degree Education ...

Machine Learning Engineer

Dearborn, MI

$105.20K - $126.30K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions -- including Generative AI and ...

Senior Machine Learning Engineer

Warren, MI · On-site +1

$222.91K - $227.20K/yr

Machine Learning Frameworks, including TensorFlow and PyTorch; Mathematical Reasoning and Probability; Programming in C++ or Python; Experience with Robot Operating System (ROS), OpenCV, or PCL;

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Junior Machine Learning Engineer information

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$29.2K

$62.6K

$95.4K

How much do junior machine learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for junior machine learning engineer in Michigan is $62,580.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,300.00 and $69,700.00 per year, depending on experience, location, and employer.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What are the most commonly searched types of Machine Learning Engineer jobs in Michigan? The most popular types of Machine Learning Engineer jobs in Michigan are:
What cities in Michigan are hiring for Junior Machine Learning Engineer jobs? Cities in Michigan with the most Junior Machine Learning Engineer job openings:
Infographic showing various Junior Machine Learning Engineer job openings in Michigan as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $62,580 per year, or $30.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

Eccalon LLC

Detroit, MI

Full-time

Posted 5 days ago


Job description

Machine Learning Engineer

Location: Detroit, MI- Onsite

Type: Full-time

Security Clearance: No clearance required, must be clearable.

Job Description

The Machine Learning Engineer will be an essential member of the Research and Development Team, where we engineer large tailor-made systems to solve complex data-related problems from many domains. At Eccalon, the projects we support often require solutions that utilize the latest and the best from Deep Learning/Machine Learning research. We support advanced projects in both data constrained and data rich settings. Qualified candidates should be driven and be able to help craft these systems as a part of our R&D team.

Responsibilities

  • Candidates are expected to be familiar with the motions of a classical Machine Learning workflow, and support the team with some of the following tasks:
    • Dataset Creation.
    • Data Exploration/Visualization.
    • Literature Review.
    • Data Wrangling.
    • Implementation and Training of Appropriate Models from Literature.
    • Characterization of Error in Models.
    • Iterative Optimization of Models.
  • On the engineering side of development, the Machine Learning Engineer will have the ability to be hands-on by:
    • Creating training and preprocessing pipelines for faster experimentation.
    • Creating algorithmic modules to interface your Models output with business requirements.
    • Integrating their code to a larger codebase.
    • Putting your model into production using AWS or GCP.

Required Qualifications

  • BS. in Computer Science, or related field.
  • 3+ years of professional Software Development experience in Python.
  • Mastery of Deep Learning fundamentals and statistics underlying Machine Learning.
  • History of software projects putting Machine Learning systems into production in any capacity.
  • History of software projects in general.
  • Deep personal interest with the complete state of the art in a subfield of Machine Learning Research.
  • Ability to work independently, and within a team.
  • Ability to communicate effectively with non-technical stakeholders and supervisors.
  • Prior project experience combining two or more of the following in a production setting:
    • Unsupervised or Semi-supervised Learning.
    • Convolutional Architectures.
    • Autoencoders.
    • Recurrent Architectures for Time-Series Applications.
    • Transformer Architectures for Natural Language Processing.
    • Generative Adversarial Architectures.

Preferred qualifications

  • MS. or PhD in Machine Learning, or related field
  • Extensive AWS or GCP experience putting scalable Machine Learning systems into production.
  • Experience working with extremely high volume / high throughput data in a data lake / data warehousing / training / production environment.
  • Has implemented cutting edge methods (e.g. a custom layer) from recent Machine Learning publications / conference proceedings and has done so in PyTorch or Tensorflow.
  • Publications in AI/ML journals or conferences.

Equal Employment Opportunity (EEO) Policy

Eccalon provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.


Eccalon logo

About Eccalon

Sourced by ZipRecruiter

We are a cross-functional collective of innovative minds that leverages technology to tackle the most challenging problems of this generation for clients, the nation, and the world. Eccalon fosters creativity, curiosity, and imagination across all departments and divisions to pioneer new ideas, products, and services. We advance innovation.​

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Hanover, MD, US

Year founded

2017