Principal Engineer with Bachelor’s Degree in Computer Science, Computer Information Systems, Information Technology, or a combination of education and experience equating to the U.S. equivalent of a Bachelor’s degree in one of the aforementioned subjects.
Job Duties and Responsibilities:
- Collaborate with data scientists, engineers, and stakeholders to develop, deploy, and maintain machine learning models in a production environment.
- Design, build, and maintain scalable and robust data pipelines to support machine learning workflows.
- Implement and manage version control, continuous integration, and continuous deployment (CI/CD) systems for machine learning models and related software components.
- Monitor the performance and health of deployed machine learning models, making necessary adjustments and improvements to ensure optimal performance and reliability.
- Develop and maintain tools and processes to automate and streamline machine learning model deployment, monitoring, and management.
- Ensure data privacy, security, and compliance with relevant regulations and best practices.
- Troubleshoot and resolve issues related to machine learning model deployment and infrastructure.
- Stay up-to-date on industry trends, emerging technologies, and best practices in MLOps, and contribute to the continuous improvement of the team's processes and tools.
- Provide technical guidance and support to data scientists and other team members on best practices for model deployment, monitoring, and management.
- Document and communicate MLOps processes, guidelines, and procedures to ensure consistency and knowledge sharing across the organization.
Technologies Involved / Skills required for the position:
- Cloud Platform: Google Cloud Platform (GCP) services, including AI Platform, Vertex AI, Dataflow, BigQuery, Cloud Storage, and Kubernetes Engine.
- Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-learn.
- Data Processing and Pipeline: Apache Beam - Dataflow, and Apache Airflow, DataProc.
- CI/CD and Version Control: Jenkins and Git.
- Containerization and Orchestration: Docker for containerization and Kubernetes with Helm.
- Experiment Tracking and Model Versioning: MLflow, DVC, or TFX for tracking experiments, managing model versions, and ensuring reproducibility.
- Monitoring and Logging: Vertex AI Monitoring.
- Programming Languages: Python, Scala.
Work location is Portland, ME with required travel to client locations throughout USA.
Rite Pros is an equal opportunity employer (EOE).
Please Mail Resumes to:
Rite Pros, Inc.
565 Congress St, Suite # 305
Portland, ME 04101.