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Entry Level Machine Learning Engineer Jobs in Kentucky

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

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Entry Level Machine Learning Engineer information

See Kentucky salary details

$26.1K

$60.2K

$102.5K

How much do entry level machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for entry level machine learning engineer in Kentucky is $60,243.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,700.00 and $68,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Kentucky? The most popular types of Machine Learning Engineer jobs in Kentucky are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Kentucky? For Entry Level Machine Learning Engineer jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Kentucky look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Kentucky are:
What cities in Kentucky are hiring for Entry Level Machine Learning Engineer jobs? Cities in Kentucky with the most Entry Level Machine Learning Engineer job openings:

Machine Learning Engineer

Purple Drive Technologies

Louisville, KY • On-site

Full-time

Posted 18 days ago


Job description

Overview:
Job Title: Machine Learning Engineer
Location: Louisville, KY
Responsibilities:
  • Build, train, and deploy ML models for business use cases (classification, NLP, CV, recommendation).
  • Preprocess and analyze large datasets.
  • Collaborate with teams to integrate ML solutions into applications.
  • Monitor and improve model performance using MLOps practices.
  • Stay updated on new AI/ML techniques and tools.

Requirements:
  • Bachelor's/Master's in CS, Data Science, or related field.
  • Strong Python skills with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Experience with data pipelines, SQL/NoSQL, and cloud platforms (AWS/GCP/Azure).
  • Knowledge of MLOps (Docker, Kubernetes, MLflow, Airflow).
  • Strong problem-solving and analytical skills.