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Entrylevel Machine Learning Engineer Jobs in Davison, MI

Data / BI Architect

Pontiac, MI · On-site

$63.25 - $81.50/hr

... Programming for data visualizations, Python, TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Databricks, Jupyter Notebooks, AWS (SageMaker, EC2, S3), Azure (Machine Learning Studio ...

... Machine Learning techniques: classification, regression, clustering, and time-series forecasting ... engineering, model evaluation, and performance tuning to ensure robust solutions • Design and ...

Machine Operator

Metamora, MI

$15.50 - $18.50/hr

Knowledge of G-Coding programming, desired. * Ability to read complex blueprints and understand GD ... Learn and grow with us through our Learning and Development training programs * We champion ...

Machine Operator

Metamora, MI · On-site

$15.50 - $18.50/hr

Knowledge of G-Coding programming, desired. * Ability to read complex blueprints and understand GD ... Learn and grow with us through our Learning and Development training programs * We champion ...

... learning. No previous experience required. Starting pay is $18.50/hour with a $1.00/hour shift ... As a leading global Tier 1 Automotive and Mobility Supplier, AAM designs, engineers and ...

Machine Operator

Lake Orion, MI · On-site

$15.75 - $18.75/hr

Learning fixturing and defixturing techniques. * Maintaining and updating equipment records ... With a unique portfolio spanning surface engineering, high-performance materials, coating equipment ...

... Entry Level Controls Engineers · Works within the scope definition and timing (due date ... AND, OR, NOT, XOR). · Mechanical -- Knowledge of machines, tools, and print reading. An ...

... Entry Level Controls Engineers · Works within the scope definition and timing (due date ... AND, OR, NOT, XOR). · Mechanical -- Knowledge of machines, tools, and print reading. An ...

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Entrylevel Machine Learning Engineer information

See Davison, MI salary details

$28.5K

$116.6K

$175.3K

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

As of Jun 9, 2026, the average yearly pay for entrylevel machine learning engineer in Davison, MI is $116,642.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,900.00 and $140,400.00 per year, depending on experience, location, and employer.

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

AspectEntrylevel Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Math, or related; some knowledge of ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, implements algorithms, collaborates with engineering teamsAnalyzes data, builds statistical models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles involve working with data and algorithms, an Entrylevel Machine Learning Engineer primarily focuses on developing and deploying machine learning models within software systems. In contrast, a Data Scientist emphasizes analyzing data, creating statistical models, and deriving insights. Both roles often require similar educational backgrounds, but their day-to-day tasks and industry applications differ.

What cities near Davison, MI are hiring for Entrylevel Machine Learning Engineer jobs? Cities near Davison, MI with the most Entrylevel Machine Learning Engineer job openings:
WMS Business Analyst/Data Scientist (Mopar Parts & Services - North America)

WMS Business Analyst/Data Scientist (Mopar Parts & Services - North America)

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 26 days ago


Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers


Job description

Key Responsibilities:
Data Engineering & Pipeline Development:
  • Design, implement, and maintain robust data pipelines (ETL/ELT) to collect, process, and transform large-scale structured and unstructured datasets from diverse automotive sources.
  • Ensure data quality, integrity, and accessibility by developing automated validation and monitoring tools.
  • Optimize data workflows for performance, scalability, and reliability, supporting both batch and real-time analytics needs.
  • Collaborate with IT and analytics teams to integrate data from business systems into centralized data products.
  • Build, train, and deploy predictive models and machine learning algorithms for applications such as performance forecasting, anomaly detection, and customer segmentation.
  • Apply best practices in data visualization to ensure clarity, accuracy, and accessibility of insights, including interactive dashboards, automated reporting, and mobile-friendly solutions.

Collaboration & Stakeholder Engagement:
  • Serve as a technical liaison between HQ analytics and business teams, translating business needs into scalable data solutions.
  • Educate and mentor team members on data best practices, analytics tools, and emerging technologies.

Basic Qualifications:
  • Bachelor's degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related field, or equivalent work experience
  • Minimum 1 year experience in data engineering, analytics, or data science (automotive industry experience preferred)
  • Proficiency in programming languages such as Python and SQL
  • Hands-on experience with ETL/ELT tools, data modeling, and cloud platforms (Snowflake, etc.)
  • Strong analytical thinking, problem-solving skills, and attention to detail
  • Excellent communication and presentation abilities, with a proven ability to explain complex technical concepts to diverse audiences
  • Ability to manage multiple priorities and deliver results in a fast-paced environment

Preferred Qualifications:
  • Master Degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related field
  • Demonstrated experience designing and deploying business dashboards and data visualizations for large-scale automotive or after-sales operations
  • Advanced proficiency with business intelligence tools (e.g., Power BI, Tableau, Qlik) and experience integrating visualizations with cloud data platforms (e.g., Snowflake)
  • Familiarity with Mopar systems and performance metrics
  • Knowledge of machine learning, deep learning, and advanced analytics techniques
  • Certifications in cloud data engineering or analytics platforms

What Stellantis employees say

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