Machine Learning jobs in United States
Algorithms Data Scientist — Real-Time Ads & Ranking
Lyft
Software Development Engineer - ML for Global Supply Chain
Amazon
GenAI Senior Data Scientist – Hybrid, Cloud & RAG
Société Financière Manuvie
Discover more opportunities than anywhere else. Find more jobs nowSenior AI Lead: Personalization & GenAI (Remote)
Instacart
Connect with headhunters to apply for similar jobsML Researcher: Deep RL & Optimization for Embodied AI
Qualcomm
Data Scientist – Center of Excellence (CoE), Personal Lines Pricing
Aviva
Data Scientist – Center of Excellence (CoE), Personal Lines Pricing
Aviva
Associate Director, Risk Based Quality Management
AstraZeneca
Algorithms Data Scientist — Real-Time Ads & Ranking
Job summary
A leading transportation media firm in Toronto is looking for an Algorithms Data Scientist to develop machine learning models for ad relevance and optimization. The role offers the chance to work with large datasets and collaborate closely with cross-functional teams. Candidates should have a Master's or PhD in a quantitative field, 3-5 years of applied science experience, and strong coding skills in Python. This position includes competitive compensation and expects in-office work at least three days a week.
Benefits
Qualifications
- 3–5 years of hands-on ML/applied science experience, ideally in production models.
- Strong proficiency in Python and machine learning frameworks.
- Experience with large-scale datasets and distributed data tools.
Responsibilities
- Design, develop, and deploy machine learning models and algorithms for Lyft Ads.
- Own the end-to-end lifecycle of modeling projects from definition to monitoring.
- Collaborate with Ads Engineering for real-time ad-serving integration.
Skills
Education
Tools
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.