Machine Learning Engineer

GCS Recruitment; Kennesaw (GA); In loco; USD 110.000 - 170.000; Tempo pieno

Descrizione del lavoro

GCS Recruitment in the United States is seeking a hands-on ML Engineer/Data Scientist to take ownership of existing production models and drive improvements in accuracy and performance. You will engineer new features, optimize pipelines, and deploy scalable ML solutions across cloud platforms.

The role emphasizes collaboration with analytics and operations teams, applying time-series forecasting, model evaluation metrics, and best practices in MLOps including Docker and Kubernetes.

Competenze

• Strong Python and SQL programming skills with hands-on ML experience.
• Experience building and evaluating predictive models and time-series forecasting.
• Proficiency with feature engineering, model optimization, and deploying ML pipelines.

Conoscenze

Python & SQL

Machine Learning & PredictiveAnalytics

Forecasting & Time-Series Modeling

Feature Eng & Model Optimization

Model Evaluation (Precision Recall F1)

PySpark / Apache Spark

MLflow, Docker, Kubernetes

AWS or Azure Cloud

Production ML deployment & maintenance

XGBoost / Scikit-Learn / LightGBM

Strumenti

XGBoost

Scikit-Learn

LightGBM

PySpark

MLflow

Docker

Kubernetes

AWS

Azure

Descrizione del lavoro

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