Machine Learning Engineer

GCS Recruitment; Shakopee (MN); On-site; USD 130,000 - 170,000; Full time

Job summary

GCS Recruitment Specialists in Minnesota is seeking a hands-on Machine Learning Engineer to own and enhance predictive models. You will work on forecasting timelines, demand, and risks using ML in production.

You will improve accuracy, engineer features, optimize performance, and deploy scalable ML solutions in AWS or Azure, with Spark and MLflow, Docker, and Kubernetes.

Qualifications

• Strong Python and SQL experience required.
• Proven ML & predictive analytics background with forecasting experience.
• Hands-on with modern ML tools (XGBoost, Scikit-Learn, LightGBM).
• Experience in time-series forecasting and feature engineering.
• Familiarity with Spark, MLflow, Docker, Kubernetes for production ML.

Skills

Python & SQL

ML & Predictive Analytics

XGBoost / Scikit-Learn / LightGBM

Forecasting & Time-Series

Feature Engineering

Model Evaluation

PySpark / Apache Spark

MLflow / Docker / Kubernetes

AWS or Azure Cloud

Production ML Deployment

Tools

Spark

MLflow

Docker

Kubernetes

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