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Junior Machine Learning Engineer Jobs in Davison, MI

Stellantis

Machine Learning Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO) . This role will leverage ...

Stellantis

Machine Learning Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO) . This role will leverage ...

Bespoke Labs

Machine Learning Engineer

Flint, MI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Whisker

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Builds and maintains CI/CD pipelines for both data engineering and machine learning model ... Mentors junior data engineers and provide technical guidance on best practices, including MLOps ...

Whisker

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Builds and maintains CI/CD pipelines for both data engineering and machine learning model ... Mentors junior data engineers and provide technical guidance on best practices, including MLOps ...

Whisker

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Builds and maintains CI/CD pipelines for both data engineering and machine learning model ... Mentors junior data engineers and provide technical guidance on best practices, including MLOps ...

Stellantis

Principal AI Engineer

Auburn Hills, MI · On-site

Bachelor's degree in AI, Machine Learning, Computer Science, Statistics, or a related field * A minimum of 8 years of professional experience in software engineering, AI, or machine learning ...

Stellantis

Principal AI Engineer

Auburn Hills, MI · On-site

Bachelor's degree in AI, Machine Learning, Computer Science, Statistics, or a related field * A minimum of 8 years of professional experience in software engineering, AI, or machine learning ...

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Junior Machine Learning Engineer information

See Davison, MI salary details

$30.3K

$65K

$99.2K

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

As of Aug 20, 2026, the average yearly pay for junior machine learning engineer in Davison, MI is $65,038.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,900.00 and $72,500.00 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.
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Machine Learning Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 2 hours ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

15th of 45 rated automakers

Job description

We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO). This role will leverage curated datasets to build a customer-level preference simulation engine, enabling optimized vehicle order guides (VOGs) for future model years.
This is a highly impactful role for an early-to-mid career data scientist who enjoys combining statistical rigor, large-scale data, and real-world business impact.
Key Responsibilities:
  • Build and run large-scale simulations (e.g., 50,000 synthetic customers) to model vehicle purchase behavior
  • Develop statistical and machine learning models using Databricks
  • Leverage datasets including:
    • Historical vehicle sales
    • Competitive sales data
    • Feature-level willingness-to-pay data
    • Customer preference models
  • Translate model outputs into optimized Vehicle Order Guides (VOGs) that inform product configuration decisions
  • Perform exploratory data analysis and feature engineering on complex datasets
  • Collaborate closely with Data Engineering to refine and leverage curated datasets
  • Communicate insights and model recommendations to business stakeholders
  • Continuously evaluate and improve model accuracy and assumptions

Basic Qualifications:
  • Bachelors Degree Required
  • Minimum 5 years of experience in data science, machine learning, or applied statistics
  • Strong experience with Databricks (critical requirement)
  • Proficiency in Python (Pandas, NumPy, scikit-learn, PySpark)
  • Strong SQL skills
  • Solid background in statistical modeling, simulation techniques, and experimental design
  • Experience translating analytical results into business decisions

Preferred Qualifications:
  • Experience with choice modeling, conjoint analysis, or demand modeling
  • Background in automotive, pricing, or product optimization analytics
  • Experience working with large-scale simulation frameworks
  • Familiarity with Spark and distributed computing
  • Exposure to MLOps or model productionization

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