ML Engineer — Forecasting & Production Model Optimization

GCS Recruitment; White Bear Lake (MN); On-site; USD 120,000 - 180,000; Full time

Job summary

GCS Recruitment is building a team that uses Machine Learning and Predictive Analytics to forecast project timelines, permit approvals, resource planning, customer demand, and operational risks. You will own existing models, improve prediction accuracy, engineer new features, optimize performance, and deploy scalable ML solutions.

The role requires strong Python/SQL, ML experience with XGBoost/Scikit-Learn/LightGBM, time-series forecasting, and hands-on work with PySpark, MLflow, Docker,

Qualifications

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

Responsibilities

• Own and improve production ML models.
• Engineer new features to boost prediction accuracy.
• Optimize model performance and scalability.
• Deploy ML solutions in scalable pipelines.

Skills

Python

SQL

Machine Learning

Predictive Analytics

XGBoost

Scikit-Learn

LightGBM

Forecasting

Time-Series Modeling

PySpark

Apache Spark

MLflow

Docker

Kubernetes

AWS

Azure

Tools

MLflow

Docker

Kubernetes

AWS

Azure

PySpark

Job description

GCS Recruitment is building a team that uses Machine Learning and Predictive Analytics to forecast project timelines, permit approvals, resource planning, customer demand, and operational risks. You will own existing models, improve prediction accuracy, engineer new features, optimize performance, and deploy scalable ML solutions.

The role requires strong Python/SQL, ML experience with XGBoost/Scikit-Learn/LightGBM, time-series forecasting, and hands-on work with PySpark, MLflow, Docker,