Full job description
Playwire is seeking a Senior Machine Learning Engineer to build and scale a next-gen website monetization platform. The role involves training, testing, deploying, and maintaining real-time predictive models, providing ML expertise to Data and Engineering teams, processing large-scale data, conducting A/B testing, designing multivariate experiments, automating model scoring, communicating analytic insights, improving modeling infrastructure, and developing advanced ML models including gradient boosted trees, graph neural networks, deep and reinforcement learning. Requirements include 5+ years in ML model development and statistical analysis, 2+ years with ML frameworks (scikit-learn, SparkML, TensorFlow, PyTorch, pandas), 2+ years with forecasting models (Prophet, ARIMA, mSSa), strong ML foundation, data processing expertise, and ability to derive insights for business decisions. Bonus qualifications include MS/PhD in quantitative fields, ad-tech experience, DevOps practices, AWS, Snowflake, and software engineering experience.
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
- 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 systems from data collection, feature selection, processing to running ML systems in production
- Ability to draw insights and conclusions from data to inform model development and business decisions
Tech stack
scikit-learnSparkMLTensorFlowPyTorchpandasProphetARIMAmSSaAWSSnowflake