What are the responsibilities and job description for the Senior Machine Learning Engineer position at Playwire?
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)
- Ad-Tech experience
- Experience with DevOps practices, CI/CD, IaC
- Experience AWS infrastructure
- Experience with Snowflake database technology
- Professional experience as a software engineer
