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Machine Learning Engineer - AI / Predictive Analytics

We're looking for a Machine Learning Engineer to join a growing AI/ML team working on predictive solutions for Comcast's construction organization.

The team is solving several interesting problems with machine learning-from predicting construction timelines and permitting delays to forecasting project costs and exploring automated construction design.

This is a hands-on role for someone who enjoys data, feature engineering, predictive modeling, experimentation, and production ML.

What You'll Be Working On

Predicting Construction Timelines
Improve an existing model that predicts how long construction jobs will take.

Predicting Permit Timelines
Build a model to estimate how long government permitting may take based on historical patterns and other predictive features.

Predicting Construction Costs
Use four years of historical labor and material expense data to predict the expected cost of future construction jobs.

Automating Construction Design
Explore machine learning approaches to help determine things such as where trenches should go, how many poles may be needed, and where cables should be placed.

ResponsibilitiesBuild, deploy, and improve machine learning models.Perform feature engineering on historical and operational data.Investigate model accuracy and identify opportunities for improvement.Build pipelines for recurring model retraining.Develop features that capture historical trends and changing behavior over time.Experiment with different predictive modeling approaches.Evaluate model performance and investigate errors.Work with production ML systems and data pipelines.Collaborate with other ML and engineering team members.Help move new ML concepts from experimentation into production.Required / Desired ExperienceMachine Learning Engineering experience.Predictive modeling experience.Strong Python.Experience with XGBoost, LightGBM, or other boosting algorithms.Feature engineering.Model evaluation.Data pipeline development.Production ML experience.AWS.MLflow or comparable experiment tracking.Strong analytical and problem-solving skills.Technology Stack

Python | AWS | XGBoost | MLflow | DVC | FastAPI | HashiCorp Nomad

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

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Machine Learning Engineer - Predictive AI

We're looking for a Machine Learning Engineer to join a team building predictive AI solutions for Comcast's construction operations.

The team already has a production ML model that predicts how long a construction job will take, and the model is currently performing well across the majority of use cases. We're looking for someone who can take ownership of the existing model, improve its performance, and help build the next generation of predictive models.

What You'll Work OnTake ownership of an existing production ML model and improve its performance across challenging use cases.Build and maintain pipelines to regularly retrain models.Analyze the cases where the current model is less accurate and determine whether additional feature engineering or specialized models can improve results.Develop predictive models around construction timelines, permitting, and project costs.Work with historical data to identify patterns that can improve predictions.Engineer features around geography, job characteristics, historical response times, seasonality, holidays, and other factors.Experiment with different modeling approaches, including XGBoost and other machine learning techniques.Track experiments and model performance using MLflow.Work closely with the team to take ML models from development into production.What We're Looking ForStrong hands-on Machine Learning Engineering experience.Experience building and improving predictive models.Strong understanding of feature engineering and model evaluation.Experience with Python and data pipelines.Experience with XGBoost or similar boosting algorithms.Experience working with production ML models.Understanding of model retraining, monitoring, and experimentation.Experience with AWS and modern ML tooling.Ability to investigate model performance and determine why certain predictions are inaccurate.Technology

Python | XGBoost | AWS | MLflow | DVC | FastAPI | HashiCorp Nomad | Machine Learning | Predictive Modeling | Feature Engineering

If you enjoy taking real-world business problems, turning them into predictive models, and then improving those models in production, this could be a great opportunity.

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

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