Production ML Engineer: Predictive AI for Construction

GCS Recruitment; Cherry Hill Township (NJ); On-site; USD 120,000 - 160,000; Full time

Job summary

GCS Recruitment is seeking a Machine Learning Engineer to support and expand a production ML environment for construction operations. You will understand existing models, improve accuracy, build data/retraining pipelines, and help move predictive solutions into production.

You'll work on problems such as construction duration, permit, and cost prediction, with an emphasis on production ML, MLOps, and AWS. Strong Python and experience with XGBoost or LightGBM are preferred.

Qualifications

• Experience in machine learning engineering and predictive modeling.
• Strong Python skills.
• Experience with XGBoost or LightGBM.
• Experience building ML/data pipelines and production ML/MLOps.
• Experience with AWS and experiment tracking (MLflow).

Responsibilities

• Analyze existing production models and identify improvements.
• Build automated model retraining pipelines.
• Perform feature engineering and analyze historical data.
• Investigate model errors and improve underperforming scenarios.
• Develop predictive models from structured/historical data.
• Deploy ML applications into production environments.
• Track experiments and model performance.
• Build data pipelines for training and feature engineering.

Skills

Machine Learning Engineering

Predictive modeling

Python

XGBoost/LightGBM

Feature engineering

Model evaluation

ML pipelines

Production ML / MLOps

AWS

MLflow

Tools

DVC

FastAPI

HashiCorp Nomad

Job description

GCS Recruitment is seeking a Machine Learning Engineer to support and expand a production ML environment for construction operations. You will understand existing models, improve accuracy, build data/retraining pipelines, and help move predictive solutions into production.

You'll work on problems such as construction duration, permit, and cost prediction, with an emphasis on production ML, MLOps, and AWS. Strong Python and experience with XGBoost or LightGBM are preferred.