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About the Role
This is an opportunity for a Principal Machine Learning Architect to help a successful ad tech company leverage ML to optimize data and elevate its platform. The role involves influencing core architectures and capitalizing on business opportunities with growing data and transaction volume, requiring a track record of large-scale end-to-end ML solutions.
Responsibilities
- Design, develop, and implement complex data-centric solutions, including large data set verification, transformation, and feature generation.
- Ensure continuous high-quality input for ML model development.
- Design and implement model delivery systems.
- Develop effective strategies for deployment and hosting of ML models.
- Manage and monitor deployed models.
- Ability to deploy fast or real-time inferencing is a plus.
Requirements
- Masters or PhD in a STEM field or equivalent experience in a Data Scientist or closely related role.
- Industry experience applying ML at scale.
- Extensive knowledge of production infrastructure and pipelines for ML models (MLOps).
- Experience with several of the following: Classification, Regression, Pattern Recognition, Recommendation Systems, Targeting Systems, Ranking Systems.
- Experience with Python or other relevant programming languages and Machine Learning frameworks.
- Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, training, and defining support procedures.
- Interest in performance optimizations.
- Deep knowledge of math, probability, statistics, and algorithms.
- Strong business acumen with the ability to work cross-functionally to source data, establish requirements, and define success.
- Experience working with an advanced engineering team.
- Knowledge of best practices for software engineering.
- Published articles or papers.
Skills
- Machine Learning
- Data Science
- MLOps
- Python
- Classification
- Regression
- Pattern Recognition
- Recommendation Systems
- Targeting Systems
- Ranking Systems
- Software Engineering
Location
- Toronto
- New York
- Montreal
- Kitchener
- London
- San Francisco
- Global
Work Type
- Full-time
- Hybrid
Experience Level
- Principal
Education Level
- Masters
- PhD
Benefits
- Comprehensive health, dental, and vision plans for you and your dependents
- Paid time off, health days, and personal obligation days
- Flexible work schedules
- Competitive retirement matching plans
- Equity packages
- Generous parental leave available to birthing, non-birthing, and adoptive parents
- Annual well-being allowance plus fitness discounts and group wellness activities
- Commuter benefits and discounts
- Employee assistance program
- Mental health first aid program
- One day of volunteer time off per year
- Donation-matching program
- Monthly town halls and regular community-led team events
- Multiple resources and programming to support continuous learning
About the Company
- Index Exchange is a globally trusted independent supply-side platform, reinventing how digital advertising works at scale.
- They are a proud industry pioneer with over 20 years of experience accelerating the ad technology evolution.
- Their proprietary tech is trusted by some of the world’s largest brands and media owners and plays a crucial role in keeping the internet open, accessible, and largely free.
- They process over 800 billion real-time auctions daily with ultra-low latency on a vertically integrated platform running on their own metal and cloud infrastructure.
- They have an engineering-first culture where engineers tackle internet-scale problems across tight-knit, global teams.
Equal Opportunity
- Index Exchange is committed to equal employment opportunities and celebrates diversity of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status.
- They welcome and encourage individuals with disabilities to apply and will make reasonable efforts to ensure accommodation requests are met throughout the recruitment process.
- Automated tools including artificial intelligence may be used to assist in screening and assessing applicants for this role, but all hiring decisions involve human review.