Senior Machine Learning Engineer

Playwire; Canada; Hybrid; CAD 120,000 - 180,000; Full time

Job summary

Playwire in Canada is seeking a Senior Machine Learning Engineer to build and scale our next-gen website monetization platform. You will deliver predictive models powering our real-time decisions and report to the head of Data.

This role requires 5+ years ML experience, in-depth knowledge of ML frameworks, and experience deploying models at scale. You will collaborate with Data and Engineering teams and contribute to experiments and model infrastructure.

Qualifications

• 5+ years of experience developing ML models and performing statistical analysis.
• Experience with ML frameworks and deploying models at scale.
• Strong data processing skills and end-to-end ownership of systems.
• Ability to extract insights to inform model development and business decisions.
• Nice to have advanced degrees in quantitative fields.

Responsibilities

• Train, test, deploy, and maintain models learning from data at high throughput in real time.
• Provide SME guidance to Data and Engineering teams on ML software engineering practices.
• Perform large-scale data processing and A/B testing on models and systems.
• Design multivariate experiments and KPI rationalization with or without controlled setups.
• Develop and implement advanced ML models, including gradient boosted trees, graph neural nets, and deep learning, to solve business problems.

Skills

ML frameworks

Forecasting models

Data processing

Model deployment

Production ML systems

Education

MS/PhD in Data Science, CS, Engineering, or related quantitative field

Tools

scikit-learn

SparkML

TensorFlow

PyTorch

pandas

Job description

Senior Machine Learning Engineer

Canada, Full-time

Full Job Description

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