3 days ago
Responsibilities
- Design, build, and ship machine learning models for messaging optimization.
- Plan and run A/B experiments in a multi-objective environment.
- Contribute to reinforcement learning systems for long-term user outcomes.
- Collaborate with product managers, data scientists, and engineers to define success metrics.
- Own the full ML lifecycle from data and modeling to deployment and monitoring.
- Integrate ML models with upstream systems and frameworks.
- Explore AI-assisted development tools to enhance experimentation and delivery.
Requirements
- Strong experience in building and deploying machine learning models in production.
- Ability to translate business problems into ML solutions.
- Experience with complex optimization problems like ranking systems.
- Hands-on experience with PyTorch and distributed systems like Ray.
- Deep understanding of experimentation and reliable test design.
- Ability to analyze results using causal inference or metric decomposition.
- Experience or curiosity about reinforcement learning and long-term optimization.
- Enjoy working across disciplines and navigating ambiguity.
Benefits
- Flexible work arrangements with the option to work from home.
- In-person meetings as needed.
Tech Stack
PyTorch
Categories
AI & MLData Science