Machine Learning Engineer

GCS Recruitment; Kent (WA); In loco; USD 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

GCS Recruitment is seeking a hands-on ML Engineer to join our data science team in Kent, WA. You will own production ML models, improve forecasts, and build scalable features and pipelines.

You will work with Python/SQL, PySpark, and cloud services (AWS or Azure) to deploy reliable solutions. Collaboration with marketing, sales, and operations will drive data-driven decisions across the business.

Competenze

• Proficient in Python and SQL with hands-on ML experience.
• Experience with ML & predictive analytics, forecasting and time-series.
• Familiarity with XGBoost, Scikit-Learn, or LightGBM.
• Knowledge of feature engineering and model optimization.
• Experience evaluating models using metrics like precision, recall, ROC-AUC, RMSE.

Mansioni

• Own existing ML models in production and improve prediction accuracy.
• Engineer new features and optimize model performance.
• Develop scalable ML solutions and deploy them in production.
• Collaborate with teams across marketing, sales, and operations to drive decisions.

Conoscenze

Python

SQL

ML & Predictive Analytics

Forecasting

Time-Series Modeling

Feature Engineering

Model Optimization

Model Evaluation

Strumenti

PySpark

MLflow

Docker

Kubernetes

AWS or 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