CA, US
Role: MLOps Engineer
Location: Remote
Duration: Fulltime
Job Description:
We are seeking a skilled MLOps Engineer to design, develop, and maintain robust MLOps pipelines on Databricks, ensuring seamless integration with Azure services. The ideal candidate will collaborate with data scientists to deploy ranking models into production, optimize search ranking algorithms, and automate CI/CD workflows to enable rapid deployment and iteration. This role involves monitoring model performance, conducting A/B testing, managing model versioning, and utilizing tools like MLflow for experiment tracking, model registry, and deployment management. Additionally, expertise in configuring and optimizing Elasticsearch for effective data indexing and querying is required.
Key Responsibilities:
Develop and maintain scalable MLOps pipelines on Databricks.
Ensure seamless integration with Azure services.
Collaborate with data scientists to deploy and optimize ranking models in production environments.
Monitor and enhance model performance through A/B testing and versioning management.
Automate CI/CD processes for efficient machine learning workflows.
Leverage MLflow for experiment tracking, model registry, and deployment operations.
Design and optimize Elasticsearch configurations for data indexing and search ranking.
Qualifications:
Proven experience with Databricks and Azure services.
Proficiency in building and maintaining CI/CD pipelines for machine learning.
Strong expertise in search ranking optimization and Elasticsearch.
Expertise in Learning to rank (Search ranking models ) in ElasticSearch.
Experience with MLflow for MLOps workflows.
Solid understanding of A/B testing and model versioning strategies