Sr. Machine Learning Engineer (Recommendation Systems)

At Philo, we’re a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented. We leverage cloud delivery, modern tech stacks, machine learning, and native app experiences on all platforms to deliver a rock solid streaming experience and explore next generation multi-screen and multi-user playback experiences. Philo’s recommendation system improves user engagement and satisfaction by tailoring content discovery to individual preferences and viewing habits, ensuring users have something to watch every time they open the app.

We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts, shaping experiences that impact millions of users. In this role, you will research, design, and build advanced algorithms and large-scale systems that power Philo’s recommendation engine. As a senior member of a growing team, you will tackle complex machine learning challenges and collaborate with data science, product, infrastructure, and backend engineering teams to deliver innovative, data-driven personalization solutions. Your work will directly impact content discovery, deepen user engagement, and drive long-term retention.

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.

Qualifications :

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.

We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We offer a generous set of benefits to support the Philo team.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

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