Crossing Hurdles

Machine Learning Engineer | Remote

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a contract basis, offering $30 - $160/hour for 10-40 hrs/week. Key skills required include Python proficiency, ETL workflow management, and machine learning expertise. Remote work is available.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
160
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🗓️ - Date
May 29, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Libraries #Python #NumPy #Programming #Data Pipeline #AI (Artificial Intelligence) #Model Evaluation #Data Ingestion #"ETL (Extract #Transform #Load)" #Data Science #ML (Machine Learning) #Pandas
Role description
Position: AI/ML Engineer Type: Contract Compensation: $30 - $160/hour Location: Remote Commitment: 10-40 hrs/week Role Responsibilities • Design, develop, and deploy machine learning models to address complex business challenges. • Collaborate with cross-functional teams to gather requirements, define data pipelines, and deliver impactful AI solutions. • Implement, optimize, and maintain ETL processes for efficient data ingestion, transformation, and management. • Utilize Python and relevant libraries to create clean, efficient, and reusable code for AI and machine learning applications. • Continuously monitor, evaluate, and enhance the performance and accuracy of deployed models. • Document processes, methodologies, and model decisions to ensure transparency and reproducibility. Requirements • Have expert-level proficiency in machine learning techniques and algorithms. • Possess advanced programming skills in Python and its data science ecosystem, including libraries such as NumPy, pandas, and scikit-learn. • Have hands-on experience designing and managing ETL workflows in production environments. • Have a strong understanding of data preprocessing, feature engineering, and model evaluation metrics. • Demonstrate a proven ability to collaborate and thrive in remote, distributed team settings. Application Process • Easy Apply on LinkedIn • Check email for next steps • Participate in resume evaluation & interview stage