Artificial Intelligence Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Artificial Intelligence Engineer with a contract length of "unknown," offering a pay rate of "unknown." Requires a Bachelor’s or Master’s degree, 8+ years in ML/AI solutions, 5+ years in Python, and cloud experience with AWS, GCP, or Azure.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 4, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Python #AWS (Amazon Web Services) #Data Science #Libraries #Computer Science #ML (Machine Learning) #Apache Spark #PyTorch #Spark (Apache Spark) #GCP (Google Cloud Platform) #Azure #TensorFlow #Data Engineering #Airflow #Cloud #Supervised Learning #Unsupervised Learning #Kafka (Apache Kafka) #Model Evaluation
Role description
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
8+ years of hands-on experience in developing and deploying ML/AI solutions.
5+ years of professional experience with Python and ML libraries such as TensorFlow, PyTorch, and Scikit-learn.
Strong understanding of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, and optimization techniques.
3+ years of experience with cloud-based AI/ML development on AWS, GCP, or Azure.
Familiarity with MLOps practices and tools.
Exposure to data engineering frameworks such as Apache Spark, Airflow, or Kafka is a plus.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
8+ years of hands-on experience in developing and deploying ML/AI solutions.
5+ years of professional experience with Python and ML libraries such as TensorFlow, PyTorch, and Scikit-learn.
Strong understanding of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, and optimization techniques.
3+ years of experience with cloud-based AI/ML development on AWS, GCP, or Azure.
Familiarity with MLOps practices and tools.
Exposure to data engineering frameworks such as Apache Spark, Airflow, or Kafka is a plus.
