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Junior Machine Learning Engineer Jobs in Michigan

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the following skills and experience. Essential * Extensive and proven track record of shipping deep ...

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Junior Machine Learning Engineer information

See Michigan salary details

$29.2K

$62.6K

$95.4K

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

As of Aug 25, 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 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 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 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.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

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 August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 80% In-person, 5% Hybrid, and 15% Remote job distribution, with an average salary of $62,580 per year, or $30.1 per hour.

Machine Learning Engineer, II - 3D Perception

Ann Arbor, MI • On-site

Socket.dev
Network Security • 1 - 10 employees

$153 - $184/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

About the Company At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Meet the Team

Torc's Multi-Modal Perception team is responsible for developing the machine learning systems that enable our autonomous trucks to perceive and understand the world around them. By combining information from cameras, LiDAR, and other sensor modalities, the team builds production-ready perception capabilities that provide the foundation for safe, reliable autonomous driving.

What You'll Do

Design, develop, and improve machine learning models supporting Torc's perception systems. Own model development and delivery for well-defined perception problem areas, from data preparation and training through evaluation and integration. Write production-quality Python and PyTorch code to support scalable training, evaluation, and inference workflows. Analyze model performance, identify failure modes, and independently troubleshoot issues to improve robustness, accuracy, and generalization. Develop and evaluate perception models leveraging multi-modal sensor data, with an emphasis on camera-based and 3D perception systems. Collaborate with software engineers, infrastructure teams, and autonomy engineers to integrate perception models into larger production software systems. Contribute to improvements in training pipelines, data workflows, experimentation tooling, and developer workflows that accelerate model iteration and deployment. Participate in model architecture discussions and contribute technical recommendations within the team. Lead small technical initiatives or model components with guidance from senior engineers. Support and mentor Machine Learning Engineer I team members on implementation, experimentation, and machine learning best practices. Document technical work, evaluation results, and design decisions to support knowledge sharing and long-term maintainability.

What You'll Need to Succeed

Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 3+ years of relevant industry experience, OR Master's degree with 1+ years of relevant experience, or equivalent practical experience. Experience developing machine learning models for computer vision, perception, robotics, autonomous systems, or a closely related domain. Strong programming skills in Python and PyTorch, with experience writing maintainable, production-quality machine learning code. Experience training, evaluating, and improving deep learning models using large-scale datasets. Experience working with image-based and/or 3D perception systems. Solid understanding of deep learning architectures commonly used for perception applications. Experience debugging model behavior, analyzing performance metrics, and proposing practical improvements. Ability to independently execute complex machine learning work within well-defined problem areas. Experience collaborating cross-functionally to integrate machine learning models into larger software systems. Strong problem-solving skills with the ability to operate effectively in an environment with evolving technical challenges and requirements. Bonus Points Experience developing perception systems for autonomous driving, robotics, or ADAS. Experience with LiDAR, point cloud processing, sensor fusion, BEV representations, or other 3D perception techniques. Experience with temporal perception models or video-based learning. Experience with C++, ROS, or robotics software development. Experience deploying machine learning models into production autonomy or robotics platforms. Experience working with large-scale perception datasets and distributed training environments. Familiarity with perception evaluation frameworks, model validation, and performance benchmarking. Experience improving ML tooling, automation, training workflows, or experimentation infrastructure. Experience leading a small technical initiative or owning a production ML component from development through deployment.

Work Location

For this position, we are open to hiring in Ann Arbor, MI, Blacksburg, VA, Fort Worth, TX office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.

Perks of Being a Full-time Torc’r
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • Company-wide holiday office closures AD+D and Life Insurance

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.

Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

Job ID: 102882 Hiring Range for Job Opening US Pay Range $153,200 — $183,800 USD

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