Machine Learning Infrastructure Specialist
2 days ago
The Senior MLOps Engineer will play a critical role in operationalizing and automating machine learning workflows, ensuring scalability, reliability, and efficiency. As part of our team, you will collaborate closely with data scientists, software engineers, and DevOps teams to deploy, monitor, and manage machine learning models in production environments.
Daily responsibilities include development and management of key system areas:
- Design, implement, and maintain scalable MLOps infrastructure and pipelines using Apache Spark, Python, and other relevant technologies.
- Collaborate with data scientists and software engineers to deploy machine learning models into production environments.
- Develop and automate CI/CD pipelines for model training, testing, validation, and deployment.
- Implement monitoring, logging, and alerting solutions to track model performance, data drift, and system health.
- Optimize and tune machine learning workflows for performance, scalability, and cost efficiency.
- Ensure security and compliance requirements are met throughout the MLOps lifecycle.
- Work closely with DevOps teams to integrate machine learning systems with existing infrastructure and deployment processes.
- Provide technical guidance and support to cross-functional teams on best practices for MLOps and model deployment.
- Stay updated on emerging technologies, tools, and best practices in MLOPs and machine learning engineering domains.
- Perform troubleshooting and resolution of issues related to machine learning pipelines, infrastructure, and deployments.
This is a unique opportunity to join Apixio's talented team and contribute to the advancement of healthcare through cutting-edge AI and machine learning solutions.
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