CBL Solutions
Principal Machine Learning Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Principal Machine Learning Engineer in Philadelphia, PA (Hybrid). The 6-month contract-to-hire position requires 5+ years in machine learning, strong Python and SQL skills, and experience with Databricks and Spark.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
July 18, 2026
π - Duration
More than 6 months
-
ποΈ - Location
Hybrid
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Philadelphia, PA
-
π§ - Skills detailed
#Documentation #Data Science #Requirements Gathering #Predictive Modeling #Data Analysis #AI (Artificial Intelligence) #Scala #Model Evaluation #AWS (Amazon Web Services) #Monitoring #Version Control #Python #Automation #MLflow #Snowflake #Programming #SQL (Structured Query Language) #Databricks #ML (Machine Learning) #Leadership #Deployment #Azure #Spark (Apache Spark)
Role description
Job Title: Principal Machine Learning Engineer
Location: Philadelphia, PA (Hybrid β Onsite Tuesday & Wednesday)
Duration: 6 Months Contract-to-Hire
Work Authorization: Must be able to convert without sponsorship. Local candidates preferred; candidates willing to relocate will also be considered.
Job Description
Seeking a Principal Machine Learning Engineer to serve as a hands-on technical leader responsible for designing, developing, deploying, and improving machine learning and applied AI solutions. This role focuses on predictive modeling, scoring, decisioning, risk detection, and production-grade ML systems while collaborating with stakeholders to solve complex business problems.
Responsibilities
β’ Design, build, validate, and optimize machine learning models for prediction, scoring, prioritization, decision support, and risk detection.
β’ Perform exploratory data analysis, feature engineering, model training, evaluation, and continuous improvement.
β’ Develop scalable, explainable, and production-ready ML solutions.
β’ Create reusable feature sets from structured and semi-structured data.
β’ Build and deploy models using Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, and related technologies.
β’ Support the complete ML lifecycle including deployment, monitoring, drift detection, retraining, and model maintenance.
β’ Translate business requirements into practical machine learning solutions.
β’ Communicate model performance, assumptions, limitations, and recommendations to both technical and business stakeholders.
β’ Maintain engineering best practices including testing, documentation, version control, and reproducibility.
β’ Provide technical leadership while remaining an active hands-on contributor.
Required Qualifications
β’ Professional experience in Machine Learning, Data Science, Applied AI, Software Engineering, or related fields.
β’ 5+ years of hands-on experience developing machine learning models.
β’ 3+ years of experience deploying and supporting production machine learning solutions.
β’ Strong programming experience with Python and SQL.
β’ Experience with ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, or AWS.
β’ Strong understanding of:
β’ Feature Engineering
β’ Model Training & Validation
β’ Model Evaluation & Calibration
β’ Thresholding & Score Interpretation
β’ Model Monitoring & Drift Detection
β’ Retraining & Production ML Lifecycle
β’ Experience translating business problems into machine learning solutions.
β’ Excellent communication skills with both technical and non-technical stakeholders.
β’ Strong software engineering practices including clean code, testing, documentation, and version control.
Preferred Skills
β’ Predictive Scoring & Scorecard Development
β’ Explainable AI & Transparent Models
β’ MLOps & Production Machine Learning
β’ Databricks & Spark Ecosystem
β’ Generative AI & AI Automation
β’ Product Development & Rapid Prototyping
β’ Stakeholder Management & Requirements Gathering
Job Title: Principal Machine Learning Engineer
Location: Philadelphia, PA (Hybrid β Onsite Tuesday & Wednesday)
Duration: 6 Months Contract-to-Hire
Work Authorization: Must be able to convert without sponsorship. Local candidates preferred; candidates willing to relocate will also be considered.
Job Description
Seeking a Principal Machine Learning Engineer to serve as a hands-on technical leader responsible for designing, developing, deploying, and improving machine learning and applied AI solutions. This role focuses on predictive modeling, scoring, decisioning, risk detection, and production-grade ML systems while collaborating with stakeholders to solve complex business problems.
Responsibilities
β’ Design, build, validate, and optimize machine learning models for prediction, scoring, prioritization, decision support, and risk detection.
β’ Perform exploratory data analysis, feature engineering, model training, evaluation, and continuous improvement.
β’ Develop scalable, explainable, and production-ready ML solutions.
β’ Create reusable feature sets from structured and semi-structured data.
β’ Build and deploy models using Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, and related technologies.
β’ Support the complete ML lifecycle including deployment, monitoring, drift detection, retraining, and model maintenance.
β’ Translate business requirements into practical machine learning solutions.
β’ Communicate model performance, assumptions, limitations, and recommendations to both technical and business stakeholders.
β’ Maintain engineering best practices including testing, documentation, version control, and reproducibility.
β’ Provide technical leadership while remaining an active hands-on contributor.
Required Qualifications
β’ Professional experience in Machine Learning, Data Science, Applied AI, Software Engineering, or related fields.
β’ 5+ years of hands-on experience developing machine learning models.
β’ 3+ years of experience deploying and supporting production machine learning solutions.
β’ Strong programming experience with Python and SQL.
β’ Experience with ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, or AWS.
β’ Strong understanding of:
β’ Feature Engineering
β’ Model Training & Validation
β’ Model Evaluation & Calibration
β’ Thresholding & Score Interpretation
β’ Model Monitoring & Drift Detection
β’ Retraining & Production ML Lifecycle
β’ Experience translating business problems into machine learning solutions.
β’ Excellent communication skills with both technical and non-technical stakeholders.
β’ Strong software engineering practices including clean code, testing, documentation, and version control.
Preferred Skills
β’ Predictive Scoring & Scorecard Development
β’ Explainable AI & Transparent Models
β’ MLOps & Production Machine Learning
β’ Databricks & Spark Ecosystem
β’ Generative AI & AI Automation
β’ Product Development & Rapid Prototyping
β’ Stakeholder Management & Requirements Gathering
