Senior Machine Learning Engineer, Philo

• 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

Desirable

• We are seeking a Machine Learning Engineer to lead the development of our recommendation system driving content discovery for millions of users
• As a member of a growing team, you will serve as both a technical leader that owns the entire stack for the recommendation system and as a subject matter expert on how to apply this system to the product to increase user engagement
• You will work closely with the data science, product, infrastructure, and backend engineering teams to create enjoyable experiences for our users that will lead to increased customer acquisition and retention
• Design ML solutions for user problems prioritized by the team and evaluate various approaches based on viability and practicality, with consideration to project timelines and available engineering resources
• Design, develop, and deploy machine learning models to improve the accuracy and relevance of our recommendations
• Identify ways the recommendation system can be integrated into the product for maximum impact
• Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback
• Collaborate with cross-functional teams comprised of data science, backend engineering, and product management to integrate ML models into the production environment
• Ensure the scalability and efficiency of our ML systems, working closely with infrastructure teams to leverage cloud technologies effectively
• Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs