Pacer Group

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer with 5–7 years of experience, offering a contract length of "unknown" and a pay rate of "unknown." It requires strong skills in Scikit-learn, Python, and PySpark, with a focus on building predictive models onsite in Philadelphia, PA.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 14, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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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
#Regression #Spark (Apache Spark) #Datasets #Data Engineering #Clustering #Programming #Classification #PySpark #ML (Machine Learning) #Python #Deployment
Role description
Machine Learning Engineer (Need a learner mindset) Location: 4 Days Onsite in Philadelphia, PA Experience: 5–7 Years About the Role We’re looking for a Machine Learning Engineer who genuinely enjoys playing with technology, experimenting with models, and solving real-world problems using data. If you love building predictive models from scratch, testing ideas, and continuously learning new ML techniques — this role is for you. What You’ll Do • Build and deploy predictive machine learning models • Work hands-on with Scikit-learn to develop and optimize ML algorithms • Use Python for model development and experimentation • Work with large datasets using PySpark • Stay updated with new ML trends and technologies Must-Have Skills • Strong experience with Scikit-learn • Solid programming skills in Python • Hands-on experience with PySpark • Experience building end-to-end ML models (data prep → training → evaluation → deployment) • Good understanding of ML concepts (regression, classification, clustering, model tuning) What We’re Looking For • 5–7 years of experience in Machine Learning / Data Engineering • Strong analytical mindset • Someone who enjoys experimenting and learning new technologies • Self-driven, curious, and solution-oriented • Comfortable working in a fast-paced environment