Machine Learning Engineer IV

Gtatelecom; West Chester (Chester County); On-site; USD 120,000 - 190,000; Full time

Job summary

Gtatelecom is seeking an experienced Machine Learning Engineer IV to lead ML solution development from research to production. You will design data pipelines, validate algorithms, deploy models, and help establish a strong technical foundation for future initiatives.

The role emphasizes cross-team collaboration, rigorous documentation, and the ability to turn ideas into reliable, scalable solutions. Strong communication skills are essential.

Qualifications

• Experience developing, refining, and validating ML or DL algorithms.
• Strong programming skills in Python, Java, or Scala.
• Experience designing data pipelines for ingestion, validation, cleaning, and monitoring.

Responsibilities

• Design, implement, refine, and validate machine learning algorithms for products and applications.
• Design and develop data pipelines for data ingestion, validation, cleaning, and monitoring.
• Train models, evaluate accuracy, and deploy validated models into production.
• Design proofs-of-concept and contribute to research for future products.
• Test solutions through case studies, technical reviews, and performance reporting.
• Collaborate with cross-functional teams to resolve technical challenges.

Skills

ML / DL algorithms

Python / Java / Scala

Data pipeline design

Production deployment

Strong programming

Education

Bachelor’s degree in CS/CE/Math/related field

Master’s degree +2–3 years related experience

Tools

Kafka

Spark

Docker

Job description

Lead the development of machine learning solutions that move from research and experimentation into real-world products and applications. As a Machine Learning Engineer IV, you’ll design data pipelines, refine and validate algorithms, deploy models into production, and help establish the technical foundation for future machine learning initiatives.

This role is a strong fit for an experienced engineer who enjoys solving complex problems and working across teams to turn ideas into reliable solutions. You’ll have the opportunity to shape proof-of-concept projects, influence technical direction, evaluate new approaches, and represent your team when addressing challenging issues. Strong communication and documentation skills will be just as important as your ability to build and monitor machine learning systems.

Required Skills & Experience

• 5–8 years of related experience after completing a bachelor’s degree, or a master’s degree with 2–3 years of related experience
• Experience developing, refining, and validating machine learning or deep learning algorithms
• Strong programming and software development skills using Python, Java, Scala, or similar languages
• Experience designing data pipelines for ingestion, validation, cleaning, and monitoring
• Experience deploying and monitoring machine learning models in production
• Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or a related technical discipline—or equivalent industry experience

Desired Skills & Experience

• Experience with data mining, statistical analysis, or advanced machine learning tools
• Knowledge of Kafka, Spark, Docker, or similar data and cloud technologies
• Experience designing proof-of-concept solutions and technical studies
• Experience collaborating with teams outside of an immediate work group
• Strong technical writing experience, including evaluation plans, white papers, reports, or technical documentation
• Experience representing a technical team in project discussions and solution development

What You Will Be Doing

• Design, implement, refine, and validate machine learning algorithms for products and applications
• Design and develop data pipelines for data ingestion, validation, cleaning, and monitoring
• Train machine learning models, evaluate accuracy, and deploy validated models into production
• Design proof-of-concept solutions and contribute to research supporting future products
• Test and evaluate solutions through case studies, technical reviews, and performance reporting
• Collaborate with cross-functional teams to resolve technical issues and provide scalable solutions

Tech Breakdown

• 30% Machine Learning Algorithm and Model Development
• 25% Data Pipeline and Cloud Engineering
• 20% Model Validation, Deployment, and Monitoring
• 15% Proofs of Concept, Testing, and Technical Evaluation
• 10% Documentation, Collaboration, and Technical Leadership

Daily Responsibilities

• Design and improve machine learning models and supporting algorithms
• Build and maintain reliable data pipelines
• Review model accuracy, performance, and production behavior
• Support model deployment, monitoring, and ongoing improvements
• Lead technical evaluations, proof-of-concept work, and case studies
• Collaborate with engineering and business teams to resolve technical challenges
• Prepare requirements, evaluation plans, reports, presentations, and other technical documentation
• Represent the team in technical discussions and solution planning