Jobs via Dice
MLOps Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer in Orlando, FL, on a W2 contract. Requires a degree in Computer Science or equivalent, strong Python skills, MLOps tools experience, and knowledge of cloud platforms. Key focus on ML model deployment and compliance.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
November 21, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Orlando, FL
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🧠 - Skills detailed
#Data Engineering #Python #Deployment #GCP (Google Cloud Platform) #Computer Science #Model Deployment #AWS (Amazon Web Services) #Docker #MLflow #TensorFlow #Cloud #Storage #Azure #Programming #Security #AI (Artificial Intelligence) #ML (Machine Learning) #Compliance #Scala #DevOps #Monitoring #Data Science #Kubernetes #PyTorch #Data Pipeline #Microservices
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Galaxy i Technologies, Inc., is seeking the following. Apply via Dice today!
Job Title: MLOps Engineer
Location: Orlando, FL
Contract role: Only on W2
W2 Only
Job Description:
As an MLOps Engineer, you will be responsible for operationalizing machine learning models and ensuring their seamless transition from development to production. You will design, implement, and maintain robust pipelines, infrastructure, and tooling that enable scalable, reliable, and secure AI/ML solutions. Working at the intersection of data science, software engineering, and operations, you will play a vital role in accelerating AI deployment while ensuring models remain effective and maintainable over time.
Primary Skills
Degree in Computer Science, Data Science, Engineering, or equivalent practical experience
Strong programming experience in Python, with knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Hands-on experience with MLOps tools such as MLflow or similar
Experience with DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes)
Knowledge of cloud platforms (Azure, AWS, Google Cloud Platform) for AI/ML services
Understanding of IT security, compliance, and governance for AI systems
Key Responsibilities:
Design, build, and manage CI/CD pipelines for ML model deployment in cloud and on-premises environments
Containerize and orchestrate ML workloads using Docker and Kubernetes
Integrate models into operational systems via APIs, event-driven workflows, or microservices
Implement model monitoring systems to track performance metrics, data drift, and prediction accuracy
Maintain model versioning and registries to ensure reproducibility and governance
Automate retraining, validation, and redeployment processes to keep models up to date
Work closely with Data Scientist to productionize experimental models
Partner with Data Engineers to design and optimize high-quality data pipelines feeding into ML models
Collaborate with DevOps and IT Security teams to ensure infrastructure compliance, scalability, and security
Optimize computing and storage resource usage for cost efficiency and performance
Note: For Immediate response please reach out to me at Sathish at galaxy i tech dot com
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Galaxy i Technologies, Inc., is seeking the following. Apply via Dice today!
Job Title: MLOps Engineer
Location: Orlando, FL
Contract role: Only on W2
W2 Only
Job Description:
As an MLOps Engineer, you will be responsible for operationalizing machine learning models and ensuring their seamless transition from development to production. You will design, implement, and maintain robust pipelines, infrastructure, and tooling that enable scalable, reliable, and secure AI/ML solutions. Working at the intersection of data science, software engineering, and operations, you will play a vital role in accelerating AI deployment while ensuring models remain effective and maintainable over time.
Primary Skills
Degree in Computer Science, Data Science, Engineering, or equivalent practical experience
Strong programming experience in Python, with knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Hands-on experience with MLOps tools such as MLflow or similar
Experience with DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes)
Knowledge of cloud platforms (Azure, AWS, Google Cloud Platform) for AI/ML services
Understanding of IT security, compliance, and governance for AI systems
Key Responsibilities:
Design, build, and manage CI/CD pipelines for ML model deployment in cloud and on-premises environments
Containerize and orchestrate ML workloads using Docker and Kubernetes
Integrate models into operational systems via APIs, event-driven workflows, or microservices
Implement model monitoring systems to track performance metrics, data drift, and prediction accuracy
Maintain model versioning and registries to ensure reproducibility and governance
Automate retraining, validation, and redeployment processes to keep models up to date
Work closely with Data Scientist to productionize experimental models
Partner with Data Engineers to design and optimize high-quality data pipelines feeding into ML models
Collaborate with DevOps and IT Security teams to ensure infrastructure compliance, scalability, and security
Optimize computing and storage resource usage for cost efficiency and performance
Note: For Immediate response please reach out to me at Sathish at galaxy i tech dot com
