About the Role
The role involves building and refining machine learning models to improve advertiser outcomes, working closely with data science and engineering teams to deliver impactful, scalable solutions.
Responsibilities
- Design and implement machine learning models to optimize advertiser acquisition and retention
- Collaborate with data scientists and engineers to integrate models into production systems
- Analyze large-scale datasets to identify patterns and opportunities for growth
- Develop scalable data pipelines to support model training and inference
- Evaluate model performance using statistical methods and real-world metrics
- Improve targeting and bidding strategies through ML-driven insights
- Work closely with product teams to define success metrics and experimentation frameworks
- Maintain and iterate on existing ML systems to adapt to changing business needs
- Ensure models are interpretable, reliable, and aligned with business goals
- Contribute to best practices in ML development and deployment
- Monitor system performance and troubleshoot issues in live environments
- Stay current with advancements in machine learning and advertising technology
- Translate business requirements into technical solutions
- Support A/B testing and causal inference initiatives
- Document models, experiments, and workflows for knowledge sharing
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexible scheduling options
Team
Part of a data science and engineering team focused on advertiser growth and monetization
Why This Role Matters
Your work will directly influence how advertisers succeed on the platform by improving targeting, conversion, and ROI through intelligent systems.
What We Look For
We value technical depth, product mindset, and the ability to turn ambiguous problems into scalable solutions using machine learning.
Available for qualified candidates requiring sponsorship
