

Senior Machine Learning Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include AI/ML development, IoT applications, cloud platforms (AWS, GCP), Python programming, and data engineering principles.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
May 31, 2025
π - Project duration
Unknown
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ποΈ - Location type
Unknown
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
San Diego, CA
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π§ - Skills detailed
#IoT (Internet of Things) #Cloud #Deployment #GCP (Google Cloud Platform) #Docker #Kubernetes #Libraries #AI (Artificial Intelligence) #Data Engineering #"ETL (Extract #Transform #Load)" #ML (Machine Learning) #Data Science #Programming #Big Data #Data Processing #AWS (Amazon Web Services) #Python
Role description
Required Skill Set:
β’ Proven experience in AI/ML development, with a focus on IoT applications and big data processing
β’ Proficiency in cloud platforms (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes)
β’ Strong programming skills in Python, with experience in data science libraries and ML frameworks
β’ Familiarity with MLOps practices and tools for experiment tracking, model versioning, and deployment
β’ 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:
β’ Proven experience in AI/ML development, with a focus on IoT applications and big data processing
β’ Proficiency in cloud platforms (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes)
β’ Strong programming skills in Python, with experience in data science libraries and ML frameworks
β’ Familiarity with MLOps practices and tools for experiment tracking, model versioning, and deployment
β’ 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.