About Oracle NetSuite
Our goal is to transform how businesses operate. We help businesses achieve their vision, no matter the size or industry. We’re the #1 cloud business software, supporting more than 40,000 organizations, in more than 100 countries. Find out more about Oracle NetSuite at www.netsuite.com.
Overview
The ML Operations team at Oracle-NetSuite is growing and we are looking for a strong, agile ML Ops Developer to help us invent the future. This team fills the role of a Data Engineering team but aims to provide ML tools as a service to downstream consumers. As part of our team, you will help design and develop infrastructure services to assist internal customers with their machine learning initiatives. Participating in design discussions with the team and contributing your ideas will give you a chance to help shape the future of our platform, while also ensuring end-to-end security and compliance concerns are met. You'll also be expected to help maintain and improve code quality by providing meaningful contributions to code reviews. If you are passionate about data, automation, and complex problem-solving, then we want to hear from you.
Career Level - IC4
Responsibilities
As an ML Ops Developer, you will play a pivotal role in building the foundation for Machine Learning at Oracle NetSuite. Key responsibilities include:
Developing and maintaining tools and APIs that help orchestrate our Machine Learning Pipelines and infrastructure: Create, scale, and optimize our ML infrastructure to enable the seamless deployment and scalability of our AI models.
Automating Machine Learning workflows, data ETL, model deployments, and monitoring: Implement robust automation solutions for the ML workflow, from data extraction and transformation (ETL) to model deployment and monitoring.
Collaboration with Data Scientists: Collaborate closely with data scientists to understand their needs, develop tools, platforms, and environments that streamline their workflow, and assist in transforming their prototypes into production-ready models.
Troubleshooting and debugging: Provide expert troubleshooting and debugging support, address issues in the infrastructure and workflow, and create robust solutions to prevent future problems.
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Proficiency in programming languages such as Python, Java, or Scala.
Proven experience in ML Ops, DevOps, Data Engineering, or a similar role.
Good understanding of cloud technologies (E.g., OCI, AWS, Google Cloud, Azure) and containerization tools (E.g., Docker).
Excellent problem-solving skills and the ability to troubleshoot complex ML infrastructure issues.
Strong communication skills, with the ability to work collaboratively in a team environment.
Nice to Have
Strong experience with ML infrastructure and technologies (E.g., TensorFlow, PyTorch, Keras).
Familiarity with ML lifecycle management tools (E.g., MLflow, Kubeflow, Kubernetes).
Experience with CI/CD tools (E.g., TeamCity, GitLab CI, CircleCI) and working with data ETL.
Disclaimer:Career Level - IC4
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Yearly based
KITCHENER, ON, Canada