AI/ML Operations (MLOps) Engineer

Placements24; Riverton (UT); On-site; USD 43,000 - 67,000; Full time

Benefits offered by this job

Competitive salary and bonuses

Health, dental, vision insurance

Career growth in MLOps

Collaborative Upington work culture

Retirement savings plan & generous PTO

Job summary

Placements24 is seeking an AI/ML Operations (MLOps) Engineer to design, implement, and manage scalable MLOps pipelines for CI/CD and deployment of ML models in production. The role bridges data science and operations, ensuring reliable model operation and automated lifecycle tasks.

You will work with AWS/Azure/GCP, Docker, Kubernetes, and ML frameworks like TensorFlow and PyTorch to monitor performance, detect drift, and drive retraining. A strong software/DevOps background is essential.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Strong experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages such as Python.
• Experience with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLflow, Kubeflow).
• Solid understanding of CI/CD principles and infrastructure as code.

Responsibilities

• Design, implement, and manage MLOps pipelines for CI/CD and deployment of ML models.
• Develop and maintain infrastructure for training, testing, and serving ML models in production.
• Implement monitoring to track model performance, drift, and retraining triggers.
• Automate operational tasks related to ML model lifecycle management.
• Collaborate with data scientists and software engineers to ensure smooth deployment and integration of ML solutions.
• Troubleshoot and resolve issues related to ML model performance and operational stability.

Skills

Python

CI/CD

MLOps

Cloud platforms

Docker

Kubernetes

ML frameworks

TensorFlow

PyTorch

Kubeflow

Education

Bachelor's or Master's degree in CS/Engineering/related field

Tools

Docker

Kubernetes

MLflow

Kubeflow

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

Our client is seeking a highly skilled AI/ML Operations (MLOps) Engineer to join their technology team in Upington. This role is crucial for building and maintaining robust, scalable, and automated systems for the deployment, monitoring, and management of machine learning models in production. You will bridge the gap between data science and operations, ensuring that our AI initiatives run efficiently and reliably. This is an exciting opportunity to work with cutting-edge AI technologies and play a key role in operationalizing machine learning at scale.

Key Responsibilities

• Design, implement, and manage MLOps pipelines for continuous integration, delivery, and deployment of ML models.
• Develop and maintain infrastructure for training, testing, and serving ML models in production environments.
• Implement monitoring solutions to track model performance, detect drift, and trigger retraining.
• Automate operational tasks related to ML model lifecycle management.
• Collaborate with data scientists and software engineers to ensure smooth deployment and integration of ML solutions.
• Troubleshoot and resolve issues related to ML model performance and operational stability.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Strong experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages such as Python.
• Experience with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLflow, Kubeflow).
• Solid understanding of CI/CD principles and infrastructure as code.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Opportunities for professional growth and specialization in MLOps.
• A collaborative and innovative work environment in Upington.
• Retirement savings plan and generous paid time off.