

Artificial Intelligence Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is an Artificial Intelligence Engineer for a 12-month remote contract, paying competitively. Requires 3+ years of AI/ML experience, proficiency in Python and frameworks like TensorFlow/PyTorch, knowledge of computer vision, and familiarity with Docker/Kubernetes.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
680
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ποΈ - Date discovered
June 5, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Remote
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
New York, NY
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π§ - Skills detailed
#Python #"ETL (Extract #Transform #Load)" #Cloud #Classification #REST API #ML (Machine Learning) #CCN (Convolutional Neural Network) #Supervised Learning #Data Enrichment #TensorFlow #AI (Artificial Intelligence) #Kubernetes #Scala #PyTorch #REST (Representational State Transfer) #Deployment #DevOps #Docker #Deep Learning #Datasets #Transformers #GCP (Google Cloud Platform) #AWS (Amazon Web Services) #Unsupervised Learning #Metadata #Data Pipeline #Neural Networks
Role description
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AI Engineer
12-month contract
Remote
We are seeking an experienced AI Engineer to join a Fortune 50 Broadcast Media & Entertainment leader located in Englewood Cliffs, NJ. In this role, you will be responsible for designing, training, and deploying machine learning models focused on video content understanding and intelligent media workflows. You will work closely with computer vision engineers and platform teams to deliver scalable AI solutions powering next-generation streaming and video analytics tools.
Minimum Qualifications:
β’ 3+ years of experience building and deploying AI/ML models in production environments
β’ Proficiency in Python and modern ML frameworks (e.g., TensorFlow, PyTorch)
β’ Strong foundation in supervised and unsupervised learning techniques
β’ Experience with model training, validation, and optimization using large-scale datasets
β’ Ability to develop and test model pipelines, including data preprocessing and feature engineering
β’ Knowledge of computer vision applications, including image and video analysis
β’ Familiarity with containerized deployments using Docker and Kubernetes
β’ Strong problem-solving and collaboration skills
Preferred Qualifications:
β’ Hands-on experience with convolutional neural networks (CNNs), transformers, or other deep learning architectures
β’ Experience working with video data pipelines and media asset metadata
β’ Knowledge of MLOps tools for experiment tracking, model versioning, and automated retraining
β’ Familiarity with REST APIs and cloud-based deployment environments (e.g., AWS, GCP)
Responsibilities:
β’ Design and train deep learning models for tasks such as video classification, object recognition, and metadata enrichment
β’ Work alongside computer vision engineers to integrate AI models into video pipelines
β’ Tune hyperparameters and validate models for performance, accuracy, and scalability
β’ Package models for deployment using Docker/Kubernetes and collaborate with DevOps for infrastructure integration
β’ Continuously monitor and retrain models based on production data and user feedback
β’ Stay up to date with the latest advancements in machine learning and computer vision research
Whatβs in it for you?
β’ Opportunity to build cutting-edge AI systems powering media intelligence and streaming innovations
β’ Collaborate with forward-thinking teams solving high-impact, real-world challenges
β’ Join a high-performance engineering environment where your work directly supports strategic initiatives
β’ Advance your skills in AI, MLOps, and large-scale deployment systems