Philo
Sr. Machine Learning Engineer (Recommendation Systems)
Philo, San Francisco, California, United States, 94199
Overview
At Philo, we build the TV experience that we want for ourselves, combining modern technology with compelling content delivery across platforms. We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts and power Philo’s recommendation engine for millions of users. You will research, design, and build advanced algorithms and large-scale systems that improve content discovery, engagement, and retention. Senior Machine Learning Engineer (Recommendation Systems) Responsibilities
Lead development of recommendation systems: design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization. Drive ML innovation at scale: analyze models and system components to ensure 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 expectations, and deliver improvements in user engagement. Advance deep learning in recommendations: apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art models. Experimentation: conduct rigorous A/B testing and ML experiments to understand model performance and iterate based on feedback. ML Vision and Roadmap: contribute to the strategic planning of the recommendations roadmap, aligning engineering with business objectives and user needs. Explore advanced architectures: experience with Two-Tower models and Deep Cross Networks (DCN) is a strong plus. Qualifications
8+ years of backend engineering and/or data science experience, with at least 4+ years focused on machine learning; experience with recommendation systems is a plus. Strong coding skills in Python; proficiency with ML frameworks like PyTorch or TensorFlow. Excellent analytical and problem-solving abilities; capable of translating complex technical challenges into business solutions. Proven track record of leading projects and delivering impactful ML solutions. Strong communication and documentation skills; able to explain complex concepts to non-technical stakeholders and document work for team learning. Experience with Amazon SageMaker or similar MLOps platforms is desirable. Status:
Full-time Location:
San Francisco, CA Compensation:
Includes annual salary between $200K - $237K depending on experience and location, company stock options and health benefits. Benefits
Full health, dental and vision coverage for you and your family 401(k) plan with employer contributions Flexible working hours Up to 20 weeks of fully paid parental leave Unlimited paid time off for vacation and sick leave $2,000 annual vacation bonus $5,250 annually for professional development and educational assistance $1,250 annual home office + TV stipend (first year) $500/month for office-based work with commuter benefits Free Gympass subscription Dog-friendly office We are an equal opportunity employer. We value a diverse and inclusive workplace and welcome people of different backgrounds, experiences, skills, and perspectives.
#J-18808-Ljbffr
At Philo, we build the TV experience that we want for ourselves, combining modern technology with compelling content delivery across platforms. We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts and power Philo’s recommendation engine for millions of users. You will research, design, and build advanced algorithms and large-scale systems that improve content discovery, engagement, and retention. Senior Machine Learning Engineer (Recommendation Systems) Responsibilities
Lead development of recommendation systems: design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization. Drive ML innovation at scale: analyze models and system components to ensure 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 expectations, and deliver improvements in user engagement. Advance deep learning in recommendations: apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art models. Experimentation: conduct rigorous A/B testing and ML experiments to understand model performance and iterate based on feedback. ML Vision and Roadmap: contribute to the strategic planning of the recommendations roadmap, aligning engineering with business objectives and user needs. Explore advanced architectures: experience with Two-Tower models and Deep Cross Networks (DCN) is a strong plus. Qualifications
8+ years of backend engineering and/or data science experience, with at least 4+ years focused on machine learning; experience with recommendation systems is a plus. Strong coding skills in Python; proficiency with ML frameworks like PyTorch or TensorFlow. Excellent analytical and problem-solving abilities; capable of translating complex technical challenges into business solutions. Proven track record of leading projects and delivering impactful ML solutions. Strong communication and documentation skills; able to explain complex concepts to non-technical stakeholders and document work for team learning. Experience with Amazon SageMaker or similar MLOps platforms is desirable. Status:
Full-time Location:
San Francisco, CA Compensation:
Includes annual salary between $200K - $237K depending on experience and location, company stock options and health benefits. Benefits
Full health, dental and vision coverage for you and your family 401(k) plan with employer contributions Flexible working hours Up to 20 weeks of fully paid parental leave Unlimited paid time off for vacation and sick leave $2,000 annual vacation bonus $5,250 annually for professional development and educational assistance $1,250 annual home office + TV stipend (first year) $500/month for office-based work with commuter benefits Free Gympass subscription Dog-friendly office We are an equal opportunity employer. We value a diverse and inclusive workplace and welcome people of different backgrounds, experiences, skills, and perspectives.
#J-18808-Ljbffr