Talent Groups
Data Science Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Science Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include proficiency in Python, GCP (Vertex AI), ML frameworks, and MLOps tools. A degree in a related field and proven ML deployment experience are required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
560
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🗓️ - Date
October 8, 2025
🕒 - 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
Weston, FL
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🧠 - Skills detailed
#Batch #C++ #GitHub #PyTorch #GIT #TensorFlow #Deployment #BigQuery #Cloud #Monitoring #Python #Docker #Kubernetes #ML (Machine Learning) #Data Engineering #Java #Data Science #Version Control #GCP (Google Cloud Platform) #AI (Artificial Intelligence) #Computer Science #Scala #Agile
Role description
Education:
• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related discipline.
Technical Skills:
• Proficiency in Python; familiarity with Java, Node.js, or C++.
• Hands-on experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Strong expertise in Google Cloud Platform (GCP), specifically Vertex AI for training, deployment, and monitoring of ML models.
• Proficiency in MLOps tools and workflows including CI/CD, Docker, Kubernetes, and orchestration frameworks.
• Solid understanding of data engineering concepts, including data warehousing and processing using BigQuery.
• Experience with version control systems such as Git and GitHub.
Professional Experience:
• Proven experience deploying ML models into production (batch and online).
• Demonstrated ability to build and maintain scalable ML pipelines end-to-end.
• Experience establishing and implementing MLOps best practices and standards.
• Background in Agile development environments with strong cross-functional collaboration skills.
Preferred Certifications (not mandatory):
• Google Cloud Professional Machine Learning Engineer
• Google Cloud Professional Data Engineer
• Google Cloud Professional Cloud Architect
Education:
• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related discipline.
Technical Skills:
• Proficiency in Python; familiarity with Java, Node.js, or C++.
• Hands-on experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Strong expertise in Google Cloud Platform (GCP), specifically Vertex AI for training, deployment, and monitoring of ML models.
• Proficiency in MLOps tools and workflows including CI/CD, Docker, Kubernetes, and orchestration frameworks.
• Solid understanding of data engineering concepts, including data warehousing and processing using BigQuery.
• Experience with version control systems such as Git and GitHub.
Professional Experience:
• Proven experience deploying ML models into production (batch and online).
• Demonstrated ability to build and maintain scalable ML pipelines end-to-end.
• Experience establishing and implementing MLOps best practices and standards.
• Background in Agile development environments with strong cross-functional collaboration skills.
Preferred Certifications (not mandatory):
• Google Cloud Professional Machine Learning Engineer
• Google Cloud Professional Data Engineer
• Google Cloud Professional Cloud Architect
