ML Engineer - Predictive Analytics for Construction

GCS Recruitment; Reston (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Comcast is seeking a hands-on Machine Learning Engineer to join our AI/ML team in Reston, VA. The role focuses on predictive analytics for construction timelines, permitting delays, and cost forecasting.

You will build and deploy ML models, perform feature engineering, and collaborate with engineers to productionize models. Responsibilities include data pipelines, model evaluation, and experiments to improve accuracy and impact.

Qualifications

• Machine Learning Engineering experience.
• Predictive modeling experience.
• Strong Python.
• Experience with XGBoost, LightGBM, or other boosting algorithms.
• Feature engineering.
• Model evaluation.
• Data pipeline development.
• Production ML experience.
• AWS.
• MLflow or comparable experiment tracking.
• Strong analytical and problem-solving skills.

Responsibilities

• Build, deploy, and improve machine learning models.
• Perform feature engineering on historical and operational data.
• Investigate model accuracy and identify opportunities for improvement.
• Build pipelines for recurring model retraining.
• Develop features that capture historical trends and changing behavior over time.
• Experiment with different predictive modeling approaches.
• Evaluate model performance and investigate errors.
• Work with production ML systems and data pipelines.
• Collaborate with other ML and engineering team members.
• Help move new ML concepts from experimentation into production.

Skills

Python

Machine Learning

Predictive modeling

Feature engineering

Data pipelines

Model evaluation

AWS

Experiment tracking

Problem solving

Tools

XGBoost

LightGBM

MLflow

DVC

FastAPI

HashiCorp Nomad

Python libraries

Job description

Comcast is seeking a hands-on Machine Learning Engineer to join our AI/ML team in Reston, VA. The role focuses on predictive analytics for construction timelines, permitting delays, and cost forecasting.

You will build and deploy ML models, perform feature engineering, and collaborate with engineers to productionize models. Responsibilities include data pipelines, model evaluation, and experiments to improve accuracy and impact.