Machine Learning Engineer

GCS Recruitment; Long Island (KS); In loco; USD 120.000 - 170.000; Tempo pieno

Descrizione del lavoro

GCS Recruitment seeks a Machine Learning Engineer to own and enhance predictive models that forecast timelines, demand, and risks. You will build features, optimize models, and deploy scalable ML solutions in production environments.

Ideal candidates have strong Python/SQL skills, experience with ML algorithms, time-series forecasting, and familiarity with PySpark, MLflow, and containerized deployments on AWS or Azure.

Competenze

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

Mansioni

• Take ownership of existing models and improve prediction accuracy.
• Engineer new features and optimize model performance.
• Deploy scalable ML solutions.
• Maintain production ML models and monitor performance.
• Collaborate with cross-functional teams to align ML initiatives.

Conoscenze

Python & SQL

ML & Predictive Analytics

XGBoost/Scikit-Learn/LightGBM

Forecasting & Time-Series

Feature Engineering

Model Evaluation

PySpark

MLflow/Docker/Kubernetes

Cloud: AWS/Azure

Production ML Deployment

Strumenti

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