Senior Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer with a contract length of "X months" and a pay rate of "$X per hour." Key skills include AI/ML development, IoT applications, Python, cloud platforms (AWS, GCP), and MLOps practices.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 26, 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
Basking Ridge, NJ
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🧠 - Skills detailed
#Cloud #Deployment #AWS (Amazon Web Services) #Big Data #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform) #ML (Machine Learning) #AI (Artificial Intelligence) #Kubernetes #Docker #Programming #Data Science #Python #Libraries #IoT (Internet of Things) #Data Engineering #Data Processing
Role description
Required Skill Set:
• Proven experience in AI/ML development, with a focus on IoT applications and big data processing
• Proficiency in cloud platforms (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes)
• Strong programming skills in Python, with experience in data science libraries and ML frameworks
• Familiarity with MLOps practices and tools for experiment tracking, model versioning, and deployment
• Knowledge of data engineering principles, including ETL processes and workflow orchestration
This position will contribute to building a new toolset that enables shared computational environments for groups of users, focusing on leveraging open-source solutions to provide comprehensive support for both data science and data engineering projects in the IoT domain.
Required Skill Set:
• Proven experience in AI/ML development, with a focus on IoT applications and big data processing
• Proficiency in cloud platforms (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes)
• Strong programming skills in Python, with experience in data science libraries and ML frameworks
• Familiarity with MLOps practices and tools for experiment tracking, model versioning, and deployment
• Knowledge of data engineering principles, including ETL processes and workflow orchestration
This position will contribute to building a new toolset that enables shared computational environments for groups of users, focusing on leveraging open-source solutions to provide comprehensive support for both data science and data engineering projects in the IoT domain.
