AdTechTalent
Data Science209 days agoOn-site

Playwire

Senior Machine Learning Engineer

machine learningml modelsstatistical analysisscikit-learnSparkMLTensorFlowPyTorchpandasProphetARIMAmSSaA/B testinggradient boosted decision treegraph neural networksdeep learningreinforcement learningAWSSnowflakedata processingmodel deploymentad-tech

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Senior

Years experience

5-10

Location

Canada

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

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