• Ph.D./MS/Bachelor s in Computer Science, statistics, or related field

• 2+ years of applied ML experience in statistical and mathematical modeling such as supervised and unsupervised machine learning, deep learning, and/or reinforcement learning; 3+ years and a Master s degree

• Track record of building, shipping and maintaining machine learning systems in a highly ambiguous and fast paced environment.

• Exposure to different ML frameworks and exposure to services like Sagemaker, Clarify, Model Monitoring, TensorFlow, MxNet, PyTorch, Sklearn, etc. preferred

• Have hands-on experience with container orchestration frameworks (e.g. Kubernetes, EKS, ECS)

• Familiarity with concepts related to testing and maintaining models in production such as A/B testing, retraining, monitoring model performance

• Hands on experience with modern data storage, messaging, and processing tools (Kafka, Flink, Spark, Hadoop, Cassandra, etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar

• Proficiency in Python is preferred. We will also consider strong quantitative candidates with a background in other programming languages such as Scala/Java

Desired:

• Experience developing products on AWS or Google Cloud Services.

• Experience in configuration management for deploying, configuring, and managing servers and systems.