Job Description

You Will: Focus on ML model load testing and creation of E2E test cases Evaluate models’ scalability and latency by running suites of metrics under different RPS and creating and automating the test cases for individual models, ensuring a smooth rollout of the models Enhance monitoring of model scalability, and handle incident of increased error rate Collaborate with existing machine learning engineers, backend engineers and QA test engineers from cross-functional teams You Bring: Advanced degree (Master’s or Ph.D.) in Computer Science/Statistics/Data Science, specializing in machine learning 3+ years of industry experience (pls don’t include years in a research group or R&D team) Strong programming skills in languages such as Java, Python, Scala Hands-on Experience in Databricks, mlFlow, Seldon Excellent problem-solving skills and analytical skills Expertise in recommendation algorithms Experience with software engineering principles, and use of cloud services like AWS Preferred Qualifications: Experience in Kubeflow, Tecton, Jenkins Experience in building and monitoring large-scale online customer-facing ML applications, preferably recommendation systems Experience working with custom ML platforms, feature store, and monitoring ML models Familiarity with best practices in machine learning and software engineering Roles and Responsibilities You Will: Focus on ML model load testing and creation of E2E test cases Evaluate models’ scalability and latency by running suites of metrics under different RPS and creating and automating the test cases for individual models, ensuring a smooth rollout of the models Enhance monitoring of model scalability, and handle incident of increased error rate Collaborate with existing machine learning engineers, backend engineers and QA test engineers from cross-functional teams You Bring: Advanced degree (Master’s or Ph.D.) in Computer Science/Statistics/Data Science, specializing in machine learning 3+ years of industry experience (pls don’t include years in a research group or R&D team) Strong programming skills in languages such as Java, Python, Scala Hands-on Experience in Databricks, mlFlow, Seldon Excellent problem-solving skills and analytical skills Expertise in recommendation algorithms Experience with software engineering principles, and use of cloud services like AWS Preferred Qualifications: Experience in Kubeflow, Tecton, Jenkins Experience in building and monitoring large-scale online customer-facing ML applications, preferably recommendation systems Experience working with custom ML platforms, feature store, and monitoring ML models Familiarity with best practices in machine learning and software engineering