AI Model Deployment Specialist
4 hours ago
A seasoned Machine Learning Operations Engineer is sought after to join Accelya's team, where they will oversee the end-to-end deployment of AI models and algorithms. This individual will be responsible for ensuring seamless integration with existing systems and automating processes to streamline the deployment pipeline.
The ideal candidate will possess a solid foundation in machine learning principles and hands-on experience with various ML frameworks. Strong problem-solving abilities, effective collaboration, and excellent communication skills are also essential for this role.
Main Responsibilities:
- Model Deployment and Integration:
- Deploy AI models into production environments, ensuring a smooth transition with existing systems.- Collaborate with software engineers to automate and optimize the deployment pipeline. - Model Monitoring and Maintenance:
- Continuously monitor AI model performance in production to guarantee correct functioning.- Set up alerts for performance degradation, model drift, and other anomalies.- Regularly update models with new data, retraining, and redeployment as necessary. - Automation and CI/CD Pipelines:
- Build, optimize, and maintain continuous integration/continuous deployment (CI/CD) pipelines for AI workflows.- Automate processes such as model versioning, testing, and deployment. - Infrastructure Management:
- Design, configure, and maintain scalable infrastructure for AI model training and inference (cloud services, on-premise hardware, Kubernetes, Docker, etc.).- Ensure high availability and efficient resource usage. - Cross-functional Collaboration:
- Work closely with data scientists to improve model performance and ensure reproducibility across different environments.- Support containerization and version control.
Key Skills:
- Technical Skills:
- Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).- Experience with cloud platforms (AWS, Azure, GCP) for deploying and managing AI workloads.- Knowledge of DevOps practices (Jenkins, GitLab CI, CircleCI) for automating AI pipelines.- Familiarity with model management tools (MLflow, DVC).- Strong experience in designing and optimizing data pipelines (Apache Kafka, Apache Spark, Airflow). - Soft Skills:
- Problem-solving abilities, particularly in productionizing AI models.- Effective collaboration and communication skills to articulate technical concepts to non-technical stakeholders.- Project management skills to prioritize tasks, manage timelines, and balance multiple responsibilities.
Compensation:
The estimated salary range for this position is $120,000 - $180,000 per annum, depending on experience.
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