Entry-Level Machine Learning Engineer
Matricstek Inc.
Dallas, TXFresher2h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 1 year · Bachelor's degree or Master's degree
- Must know
- Machine learningPythonData structures & algorithmsStatisticsscikit-learnPandas
- Nice to have
- AWSAzureGCP
- Work
- On-site in Dallas
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning87%Python85%Statistics33%Data structures & algorithms23%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 10, 2026 · still open
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About the Role
We are looking for a motivated and enthusiastic Entry-Level Machine Learning Engineer to join our team. This role offers an opportunity to work on real-world projects, develop AI/ML solutions, and collaborate with experienced professionals.
Key Responsibilities
- Develop, train, test, and evaluate machine learning models using Python.
- Collect, clean, preprocess, and analyze structured and unstructured datasets.
- Implement machine learning algorithms for classification, regression, clustering, and prediction tasks.
- Work with libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib.
- Assist in developing deep learning and AI-based solutions using TensorFlow or PyTorch.
- Evaluate model performance, troubleshoot issues, and improve accuracy.
- Collaborate with data engineers and software developers to integrate ML models into applications.
- Document experiments, findings, and model development processes.
Requirements & Tech Stack
- Basic to intermediate knowledge of Python programming.
- Understanding of machine learning algorithms and fundamental statistical concepts.
- Familiarity with NumPy, Pandas, Scikit-learn, and data visualization tools.
- Knowledge of SQL and database fundamentals.
- Understanding of data preprocessing, feature engineering, model evaluation, and validation techniques.
- Basic familiarity with TensorFlow, PyTorch, or other deep learning frameworks.
- Strong analytical, problem-solving, and communication skills.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Statistics, Mathematics, or a related field.
- Academic projects, internships, or personal projects in machine learning or artificial intelligence.
- Familiarity with Git/GitHub and Jupyter Notebook.
- Basic knowledge of cloud platforms such as AWS, Azure, or Google Cloud is a plus.