Senior Machine Learning Engineer

About The Team 

Our team’s mission is to build cutting-edge advertising technology to support and help grow a sustainable advertising business. The team owns server technologies, data, and cloud services for advertising.

About the role 

The Advertising Performance team at Roku is looking for seasoned back-end engineers with a background in machine learning to improve our ad experiences. Examples of such problems include improving ad relevance, inferring demographics, yield optimization, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using code for tool building, statistical analysis, and modeling, using both general purpose software and statistical languages.” 

What you'll be doing

• ML-Infrastructure: Help build a first-class machine learning platform from the ground up which helps manage the entire model lifecycle: feature engineering, model training/evaluation, versioning, deployment/online serving and monitoring prediction quality.
• Data Analysis/Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models.
• Model training with batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Decision Trees, Logistic Regression, Bayesian Analysis, Neural Networks and others to develop and evaluate algorithms to improve product/system performance, quality and accuracy.
• Low level systems debugging, performance measurement & optimization on large production clusters.

  We're excited if you have

• First-hand experience in applied machine learning on real use cases (brownie points for ad-tech related use cases!).
• Experience with ML/distributed ML frameworks like Spark-MLlib, TensorFlow etc.
• Experience with real-time scoring/evaluation of models with low latency constraints.
• Great coding skills and strong software development experience (we use Spark, Python and Java a lot).
• Can work with large scale computing frameworks, data analysis systems and modeling environments. Examples include technologies like Spark, Hive, NoSQL stores etc.
• Bachelors, Masters or PhD program in Computer Science/Statistics or a related field.
• Ad-tech background is a plus.