Senior Machine Learning Engineer, Recommendations

Posted 13 Days Ago
Culver City, CA
166K-207K Annually
Senior level
Digital Media • eCommerce • Gaming • Mobile • News + Entertainment
The world’s largest destination for anime & manga focused on creating 360° fan experiences.
The Role
Senior Machine Learning Engineer responsible for designing and implementing recommendation systems to enhance user engagement and satisfaction through personalized content recommendations. Will work on system architecture, data preprocessing, model training, measurement feedback, and operational excellence. Requires 5+ years of experience in large-scale recommendation systems, proficiency in Python, familiarity with TensorFlow, PyTorch, GPU optimization, and cloud platforms.
Summary Generated by Built In
About Crunchyroll

WE HELP EVERYONE BELONG. IT’S OUR PURPOSE.

Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.

Join our team, and help us shape the future of anime!

About the role

In the role of Senior Machine Learning Engineer, you will report to the Director of data science and machine learning in the Center for Data and Insights.

We are considering applicants for the location(s) of Culver City, California.

We are looking for a Senior Machine Learning Engineer to join our team to create personalized content recommendations for our tens of millions of customers around the world. The main mission is to help customers discover contents they will love, from our must-watch simulcast season of shows to our library of classics and niche titles, and further beyond into theatrical release, merchandise, music, and games, etc that covers the anime fandom and lifestyle. Your work will have a meaningful effect, enhancing user engagement and satisfaction by tailoring the content experience to individual tastes and preferences. This role offers a greenfield opportunity to develop the latest recommendation algorithms to delight a fast-growing global audience.

Core Responsibilities

  • System Architecture: Design and develop scalable, robust architectures for the recommendation system.

  • Data Sense and Awareness: Identify, collect, and preprocess data from various sources to build comprehensive user profiles and content attributes.

  • Model Training and Operations: Experiment, train, and deploy machine learning models that power personalized recommendations.

  • Measurement and Feedback Loop: Implement systems to measure the effectiveness of recommendations and incorporate user feedback to improve model performance.

  • Operational Excellence: Ensure the reliability, efficiency, and scalability of the recommendation system through best practices in coding, testing, and deployment.

We are considering applicants for the location of Los Angeles, California. 

About You

  • 5+ years of experience in designing and implementing large-scale recommendation systems.

  • You have a background in machine learning and recommendation system algorithms

  • Proficiency in Python

  • You have experience with frameworks like TensorFlow, PyTorch, or similar.

  • You have familiarity with GPU optimization and cloud computing platforms (AWS, Google Cloud, Azure).

  • You have demonstrated ability to work with cross-functional teams including Engineering, Product, Content Acquisition and Programming, Consumer Insights, to name a few.

  • You have experience conveying complex technical concepts to non-technical stakeholders.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

  • Receive a great compensation package including salary plus performance bonus earning potential, paid annually.

  • Flexible time off policies allowing you to take the time you need to be your whole self.

  • Generous medical, dental, vision, STD, LTD, and life insurance

  • Health Saving Account HSA program

  • Health care and dependent care FSA

  • 401(k) plan, with employer match

  • Employer paid commuter benefit

  • Support program for new parents

#LifeAtCrunchyroll #LI-Hybrid

The Pay Range for this position is listed. Actual pay will vary based on factors including, but not limited to location, experience, and performance. The range listed is just one component of Crunchyroll’s Total Rewards offerings for employees. Other rewards may include performance bonuses, employer matched retirement savings, time-off programs, and progressive health benefits and perks.

Pay Transparency - Culver City, CA

$165,867$207,334 USD

About our Values

We want to be everything for someone rather than something for everyone and we do this by living and modeling our values in all that we do. We value

  • Courage. We believe that when we overcome fear, we enable our best selves.

  • Curiosity. We are curious, which is the gateway to empathy, inclusion, and understanding.

  • Service. We serve our community with humility, enabling joy and belonging for others.

  • Kaizen. We have a growth mindset committed to constant forward progress.

Our commitment to diversity and inclusion

Our mission of helping people belong reflects our commitment to diversity & inclusion. It's just the way we do business.

We are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Crunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japan's Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation.

Questions about Crunchyroll’s hiring process? Please check out our Hiring FAQs: https://help.crunchyroll.com/hc/en-us/articles/360040471712-Crunchyroll-Hiring-FAQs

Please refer to our Candidate Privacy Policy for more information about how we process your personal information, and your data protection rights: https://tbcdn.talentbrew.com/company/22978/v1_0/docs/spe-jobs-privacy-policy-update-for-crpa-dec-21-22.pdf

Please beware of recent scams to online job seekers. Those applying to our job openings will only be contacted directly from @crunchyroll.com email account.

Top Skills

Python

What the Team is Saying

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The Company
HQ: San Francisco, CA
1,200 Employees
Hybrid Workplace
Year Founded: 2006

What We Do

Crunchyroll is the world’s largest destination for anime and manga focused on creating 360° experiences — from video to merchandise, events, and gaming — for fans to connect through the content they love.

Why Work With Us

The quality of our company is a direct result of the quality of our people, so we take the process and art of hiring very seriously. Every position we recruit against is an opportunity for us to enhance and directly impact our culture and climate, and it is a reflection of the values we uphold.

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Crunchyroll Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Two in-person days per week. Tuesdays and Thursdays are the company-wide days for ALL team members to be in the office, and individuals may choose to come in more if the please.

Typical time on-site: 2 days a week
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