Machine Learning Engineer - Production ML​/AI

Machine Learning Engineer - Production ML/AI

We're hiring a Machine Learning Engineer to help support and expand a growing production ML environment focused on Comcast's construction operations.

This role is ideal for someone who enjoys more than just building models. You'll be responsible for understanding existing models, improving their accuracy, building data/retraining pipelines, and helping move predictive solutions into production.

The team currently has a production model that predicts how long construction jobs will take and is looking to improve the model while expanding into additional predictive use cases.

You'll work on several machine learning problems, including:

Construction Duration Prediction
Improve an existing production model that predicts how long construction work will take.

Permit Prediction
Develop a model to predict how long it may take to obtain government permits required for construction.

Cost Prediction
Build a predictive model using historical material and labor expenses to estimate the cost of future construction work.

Automated Construction Design
Explore ML approaches that could help automate aspects of construction design, including trench placement, poles, and cable layouts.

• Analyze existing production models and identify opportunities for improvement.
• Build automated model retraining pipelines.
• Perform feature engineering and analyze historical data.
• Investigate model errors and develop solutions for underperforming scenarios.
• Determine when additional features are appropriate versus when a specialized model may be needed.
• Develop predictive models using structured and historical data.
• Build data pipelines supporting model training and feature engineering.
• Track experiments and model performance.
• Deploy and integrate ML applications into production environments.

• Machine Learning Engineering experience.
• Experience with predictive modeling
  .
• Strong Python experience.
• Experience with XGBoost, LightGBM, or similar ML algorithms
  .
• Feature engineering and model evaluation.
• Experience building ML/data pipelines.
• Production ML / MLOps experience.
• AWS experience.
• MLflow or similar experiment-tracking experience.
• Strong problem-solving skills and the ability to investigate why models succeed or fail.

AWS | Python | XGBoost | MLflow | DVC | FastAPI | Hashi Corp Nomad

This is a great opportunity for someone who wants to work on real predictive AI problems with measurable business impact
, rather than purely theoretical ML research.

GCS is acting as an Employment Business in relation to this vacancy.