Machine Learning Engineer

GCS Recruitment; Whitehall (Lehigh County); On-site; USD 120,000 - 180,000; Full time

Job summary

GCS Recruitment is seeking an ML Engineer to own existing models and drive improvements in accuracy and scalability. You will engineer features, optimize models, and deploy scalable ML solutions across forecasting and demand planning domains.

The role emphasizes collaboration with data, engineering, and operations teams to deliver reliable predictive insights and robust machine learning workflows.

Qualifications

• Strong Python and SQL experience.
• Proficient in ML and predictive analytics.
• Experience with XGBoost, Scikit-Learn, or LightGBM.
• Forecasting and time-series modeling.
• Feature engineering and model optimization.
• Experience deploying production ML models.
• Experience with PySpark / Apache Spark.
• Familiar with MLflow, Docker, and Kubernetes.
• Experience with AWS or Azure cloud.

Responsibilities

• Own existing ML models and improve prediction accuracy.
• Engineer new features to boost forecasting performance.
• Optimize model performance and scalability for production.
• Collaborate with teams to deploy scalable ML solutions.

Skills

Python

SQL

Machine Learning

Predictive Analytics

Forecasting

Time-Series

Feature Engineering

Model Optimization

Model Evaluation

PySpark

Docker

Kubernetes

MLflow

AWS/Azure

Production ML

Tools

XGBoost

Scikit-Learn

LightGBM

Job description

Role Overview

We're working with a team that uses Machine Learning and Predictive Analytics to forecast project timelines, permit approvals, resource planning, customer demand, and operational risks. These predictions help drive key business decisions across marketing, sales, and operations.

The team already has machine learning models in production and is looking for someone who can take ownership of existing models, improve prediction accuracy, engineer new features, optimize performance, and deploy scalable ML solutions.

Required Skills

• Strong Python and SQL experience
• Machine Learning and Predictive Analytics
• XGBoost, Scikit-Learn, LightGBM, or similar algorithms
• Forecasting and Time-Series Modeling
• Feature Engineering and Model Optimization
• Model Evaluation (Precision, Recall, F1, ROC-AUC, MAE, RMSE)
• PySpark / Apache Spark
• MLflow, Docker, Kubernetes
• AWS or Azure Cloud
• Experience deploying and maintaining production ML models

Preferred Background

• Demand Forecasting
• Customer Churn Prediction
• Revenue Forecasting
• Risk Scoring
• Resource Planning
• Pricing Optimization
• Capacity Planning
• Supply Chain Analytics
• Operational Forecasting