Senior Machine Learning Operations Architect
4 days ago
At Canopy, we're revolutionizing vehicle security by building cutting-edge technology. As a Staff MLOps Engineer, you'll play a critical role in leading the design, development, and implementation of scalable machine learning operations (MLOps) pipelines and infrastructure.
About the RoleThis is a high-impact opportunity to shape the future of MLOps at Canopy. You'll work closely with cross-functional teams to streamline and automate data ingestion, model deployment, ensuring high availability, reliability, and performance of AI-driven solutions.
Key Responsibilities- MLOps Pipeline Development: Design, implement, and maintain robust MLOps services and pipelines to automate the deployment and monitoring of machine learning models in production.
- Collaboration and Integration: Work with engineers to integrate machine learning models into existing systems and workflows, ensuring seamless integration with cloud or on-premises infrastructure.
- CI/CD Best Practices: Develop and enforce best practices for continuous integration and continuous delivery (CI/CD) in machine learning projects, including version control, automated testing, and continuous integration.
- Model Performance Monitoring: Monitor the performance and health of data and models in production, implementing strategies for retraining, versioning, and rollback when necessary.
- Infrastructure Optimization: Optimize infrastructure for model training and inference, ensuring scalability, efficiency, and cost-effectiveness.
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- 8+ years of experience in software engineering, data engineering, or a related field, with at least 3 years specifically in MLOps.
- Strong programming skills in languages such as Python, Java, or C/C++.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Proficiency in DevOps tools and practices, including Docker, Kubernetes, and CI/CD pipelines.
We offer a comprehensive benefits package, including medical, dental, and vision coverage, as well as retirement plan matching. The estimated salary range for this position is $129,200 - $180,500, depending on skills and experience.
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Detroit, Michigan, United States Canopy Full timeSenior MLOps Engineer at CanopyWe are seeking an experienced Senior MLOps Engineer to lead the design and implementation of scalable machine learning operations pipelines and infrastructure.As a Staff MLOps Engineer at Canopy, you will be responsible for ensuring that machine learning models are efficiently deployed, monitored, and maintained in production...
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