NextGen | GTA: A Kelly Telecom Company
Consultant I (Contractor)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Consultant I (Contractor) focused on Machine Learning Engineering, requiring expertise in Python, scikit-learn, and PySpark. The contract length is unspecified, with a competitive pay rate. Key skills include ML model deployment, MLOps practices, and cloud familiarity.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 20, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Philadelphia, PA
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🧠 - Skills detailed
#Spark (Apache Spark) #Model Evaluation #Big Data #Datasets #Scala #Automation #Libraries #ML (Machine Learning) #Deployment #Pandas #A/B Testing #Model Validation #Python #Matplotlib #MLflow #NumPy #Model Deployment #PySpark #GitHub #Cloud
Role description
Machine Learning Engineer - Python & Big Data Stack
We're seeking a Machine Learning Engineer to develop and deploy scalable ML solutions using Python frameworks and big data technologies.
Key Responsibilities
• Build ML models using scikit-learn and process large datasets with PySpark
• Deploy models to production and monitor performance
• Implement feature engineering, model validation, and A/B testing
• Maintain ML infrastructure and ensure model reliability
Required Skills
• Strong experience with scikit-learn and PySpark
• Proficiency in Python and ML libraries (pandas, numpy, matplotlib, polars)
• Experience with MLflow for experiment tracking and model management
• Knowledge of GitHub Actions for ML pipeline automation
• Experience with model deployment and MLOps practices
• Understanding of statistical methods and model evaluation
• Familiarity with cloud platforms and containerization
Posted By: Nicole Screnci
Machine Learning Engineer - Python & Big Data Stack
We're seeking a Machine Learning Engineer to develop and deploy scalable ML solutions using Python frameworks and big data technologies.
Key Responsibilities
• Build ML models using scikit-learn and process large datasets with PySpark
• Deploy models to production and monitor performance
• Implement feature engineering, model validation, and A/B testing
• Maintain ML infrastructure and ensure model reliability
Required Skills
• Strong experience with scikit-learn and PySpark
• Proficiency in Python and ML libraries (pandas, numpy, matplotlib, polars)
• Experience with MLflow for experiment tracking and model management
• Knowledge of GitHub Actions for ML pipeline automation
• Experience with model deployment and MLOps practices
• Understanding of statistical methods and model evaluation
• Familiarity with cloud platforms and containerization
Posted By: Nicole Screnci
