Senior Machine Learning Engineer, Philo
Recommendation Systems
$200-237k
Offers company stock options
Live TV streaming service
Be an early applicant
Live TV streaming service
101-200 employees
Be an early applicant
$200-237k
Offers company stock options
101-200 employees
Company mission
To provide affordable and accessible television streaming services to everyone.
Role
Who you are
- 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
What the job involves
- 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
- 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
Our take
Streaming services offer cheaper options than cable TV packages, but prices are beginning to rise. This is partly due to packages beginning to bundle costly sports and other media packages that viewers do not necessarily want.
Philo offers a streaming service that aims to provide a streamlined selection of channels as an affordable, yet comprehensive, viewing option. The streamlined and high-quality channel offerings are available to viewers at $25 per month, a price significantly lower than standard cable subscriptions, with the base option including 60 live channels and over 75,000 on-demand offerings.
Whilst other streaming platforms offer affordable packages, Philo stands out with unique features such as a co-viewing service that allows up to three people to watch the same program together. The company has also proven its dedication to improved user experiences, as it expands its compatibility with devices such as smart TVs.
Steph
Company Specialist at Welcome to the Jungle
Insights
10% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Aug 2020
$50m
SERIES D
Jul 2018
$41.4m
SERIES C
Total funding: $155.7m
Company benefits
- 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!
Company HQ
Telegraph Hill, San Francisco, CA
Leadership
Andrew McCollum
(CEO, not founder)Studied Computer Science at Harvard before co-founding Facebook. Joined Philo in 2014 and has acted as CEO since.
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