Machine Learning Engineer III

Machine Learning Engineer Job at a Glance Title: ML Engineer Location: Philadelphia, PA Contract: W2 only, 5-month contract with potential for extension or conversion to full-time with either the client or CEI Pay: $80/hour + optional medical, dental, vision, 401(k) match Role Overview We are seeking a mid-level Machine Learning Engineer to help evolve an existing predictive analytics solution into a more advanced, field-driven model. The current system predicts average job duration for large-scale construction and operational work, and this role will focus on building a new predictive model that incorporates a broader and richer set of job attributes to improve accuracy and business value. This is a hands-on role suited for a solid machine learning engineer with practical experience in Python, PySpark, and common machine learning technologies working with structured, large-scale data. Responsibilities Design, develop, and enhance predictive machine learning models focused on estimating job duration and operational timelines Build a new model leveraging diverse job-level fields and historical data to improve forecasting performance Perform feature engineering, data preparation, and exploratory analysis across large datasets Develop and train models using Python and PySpark in distributed environments Evaluate model performance using appropriate statistical and machine learning metrics Collaborate closely with data engineers, analytics teams, and stakeholders to translate business objectives into modeling solutions Support model deployment, testing, and ongoing performance monitoring Maintain clear documentation of modeling approaches, assumptions, and results Required Qualifications 3+ years of professional experience as a Machine Learning Engineer, Data Scientist, or similar role Strong proficiency in Python for data analysis and machine learning Hands-on experience with PySpark and distributed data processing frameworks Solid understanding of core machine learning concepts, including: Regression and predictive modeling techniques Feature engineering and data preprocessing Model evaluation, validation, and performance tuning Experience working with structured datasets and production-oriented ML workflows Preferred Qualifications Experience improving or replacing existing machine learning models Familiarity with Spark MLlib, scikit-learn, pandas, and NumPy Exposure to MLOps, model deployment, or monitoring practices Experience working with operational, construction, logistics, or time-based forecasting data Ability to communicate technical findings to non-technical stakeholders What You’ll Deliver A next-generation predictive model that improves job duration forecasting Scalable, maintainable ML pipelines aligned with enterprise data platforms Well-documented and reproducible machine learning solutions Strong collaboration across engineering and analytics teams #ZR #INDGEN