ML Engineer I: Data Pipelines & Production Models

Gtatelecom; West Chester (Chester County); On-site; USD 70,000 - 105,000; Full time

Job summary

Gtatelecom is seeking an entry‑level Machine Learning Engineer to transform algorithms into working products. You will build data pipelines, train models, validate accuracy, and support production deployments using Python, Java, Scala, cloud tech and modern data tools.

This hands‑on role blends model development, data engineering, testing, and technical research, with opportunities to contribute to POC projects and document findings for production teams.

Qualifications

• 1–3 years of related experience after completing a bachelor’s degree.
• Experience with machine learning, deep learning, data mining, or statistical analysis.
• Strong programming and software development skills.
• Familiarity with Python, Java, or Scala.
• Experience building or supporting data pipelines, including data ingestion, validation, cleaning, and monitoring.
• Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or a related technical discipline—or equivalent industry experience.

Responsibilities

• Implement, refine, and validate machine learning algorithms for products and applications.
• Build and maintain data pipelines for ingestion, validation, cleaning, and monitoring.
• Train machine learning models and evaluate their accuracy and performance.
• Deploy validated models into production and support ongoing monitoring.
• Contribute to proof‑of‑concept projects, case studies, testing, and technical evaluations.
• Research and prepare documentation, requirements, reports, presentations, and recommendations.

Skills

ML experience

Programming skills

Python/Java/Scala

Education

Bachelor's degree in CS/CE/Math

Tools

Kafka

Spark

Docker

Job description

Gtatelecom is seeking an entry‑level Machine Learning Engineer to transform algorithms into working products. You will build data pipelines, train models, validate accuracy, and support production deployments using Python, Java, Scala, cloud tech and modern data tools.

This hands‑on role blends model development, data engineering, testing, and technical research, with opportunities to contribute to POC projects and document findings for production teams.