Sr. Machine Learning Engineer (Recommendation Systems)

Philo is a technology company focused on revolutionizing the television experience through modern technology and machine learning. They are seeking a Senior Machine Learning Engineer to lead the development of their recommendation systems, enhancing user engagement and satisfaction by personalizing content discovery. This role involves researching, designing, and building advanced algorithms and collaborating with various teams to deliver innovative solutions.

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
• Explore advanced architectures: Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus

Requirements:

• 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
• Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow
• 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
• Experience with Amazon SageMaker or similar MLOps platforms
• Experience with recommendation systems is a big plus
• Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus