Philo's recommendation system improves user engagement and customer satisfaction by tailoring content discovery to individual preferences and viewing habits. We want users to be confident that Philo will have something they want to watch every time they open the app.
Requirements
- Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow.
- Experience with Amazon SageMaker or similar MLOps platforms
- Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus.
Responsibilities
- Lead development of recommendation systems: Design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization.
- Drive ML innovation at scale: Conduct deep dives into models and system components, ensuring performance, scalability, and robustness across regions and product areas.
- Own the ML pipeline: Build and maintain reliable pipelines for data extraction, feature engineering, model training, testing, and deployment.
- Collaborate with Product, Data Science & Engineering: Translate product requirements into ML solutions, set clear expectations, and deliver measurable improvements in user engagement.
- Advance deep learning in recommendations: Apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art recommendation models.
- Experimentation: Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback.
- ML Vision and Roadmap: Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs.
Other
- 8+ years of experience in backend engineering and/or data science, including 4+ years focused on machine learning. Experience with recommendation systems is a big plus.
- Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions.
- Proven track record of leading projects and delivering impactful machine learning solutions.
- Strong communication and documentation skills; capable of explaining complex, technical concepts to non-technical stakeholders and to diligently document your work to help the team as a whole learn and move quickly.
- Full-time
- Location: San Francisco, CA
