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 - in short, we're building the TV experience that we've always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences.
Senior Machine Learning Engineer (Recommendations)

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.

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.
Responsibilities:

• 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.

Qualifications:

• 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.

Nice to have:

• Experience with Amazon SageMaker or similar MLOps platforms.

Status: Full-time
Location: San Francisco, CA
Compensation: Includes annual salary between $200K - $240K 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 believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team:

• Full health, dental and vision coverage for you and your family
• 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay)
• 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 (we pay you to take a two week vacation)
• $5,250 annually for professional development and educational assistance
• $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter)
• $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco)
• Free Gympass subscription - an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps
• Dog-friendly office
• And much more!

For California Residents: Philo's CCPA Notice at Collection - Employees, Applicants, Owners, Directors, Officers and Contractors

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