Playwire is seeking a Senior Machine Learning Engineer to join our team and help build out and scale our next-gen website monetization platform. Reporting to the head of Data, this hands-on engineering role will focus on delivering a portfolio of predictive models and inferential decision assets powering our real time platform.
Essential Functions: (What you'll do)
Train, test, deploy, and maintain models that learn from data across hundreds of thousands of interactions per second to predict future behaviors in real time
Provide SME guidance for Data and Engineering teams on ML software engineering principles, model deployments, and platform capabilities
Process data and information at a massive scale, and perform A/B testing tasks on statistical models, ML algorithms, and deployed systems
Design and execution of multivariate experiments, KPI rationalization, establish measurement protocols with and without controlled setup, arbitrate over statistical and business significance
Build and Deploy capabilities for automating model scoring/Inferencing of ML models
Communicate complex analytic findings and insights effectively to stakeholders at all levels
Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load
Develop and implement advanced ML models, such as gradient boosted decision tree, graph neural networks, deep and reinforcement learning models, to solve critical business problems
Requirements: (Qualifications)
5+ years related experience with developing machine learning models and conducting statistical analysis
2+ years experience & proficiency with ML frameworks such as scikit-learn, SparkML, TensorFlow, PyTorch, pandas, etc.
2+ years experience with forecasting models such as Prophet, ARIMA, and mSSa
Strong foundation in Machine Learning, with a proven track record of developing and deploying ML models at scale
Strong background in data processing and can demonstrate strong data intuition and end-to-end ownership of our systems - from data collection, feature selection, and processing to running ML systems in production
Ability to draw insights and conclusions from data to inform model development and business decisions
Nice to have: (Bonus)
MS or PhD in Data Science, Computer Science, Engineering, Statistics, Economics, Physics or related quantitative field (e.g. Econometrics, Mathematics)