Senior Machine Learning Engineer, Recommendation and Personalization

About the role

In the role of Senior Machine Learning Engineer for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in the Center for Data and Insights, working from the Los Angeles or San Francisco area in California. You will lead the research, development, and test of advanced models, and work together with product and engineering partners to deliver tailored experiences for our fans across the anime ecosystem, including anime video recommendations, digital manga suggestions, merchandise personalization, anime-themed gaming, music, and more.

This position will collaborate closely with scientists, engineers, and product owners to prototype innovative algorithms, evaluate their impact, and integrate them into production systems that drive user engagement, retention, discovery, and satisfaction. We work a hybrid schedule, in-office three days a week: Tuesday, Wednesday, Thursday.

• Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, deep learning, and generative recommendation approaches to personalize content discoveries.
• Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment using scalable cloud platforms with engineers.
• Optimize models for accuracy, latency, and scalability to handle massive user interaction data from streaming and multi-platform, multi-domain experiences across the fandom.
• Integrate personalization solutions with other services, and implement monitoring for model performance, bias detection, and automated retraining.
• Collaborate on A/B testing, experimentation, and iterative improvements to refine recommendations based on user feedback and evolving content trends.

Requirements

We get excited about candidates who have:

• Experience: 8+ years of hands-on experience in applied machine learning, with a proven track record in building recommendation systems or personalization engines, ideally in media, entertainment, or e-commerce platforms.
• Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks, or similar. Experience with big data tools (e.g., Spark) and cloud infrastructure (e.g., AWS/GCP) for handling large-scale datasets.
• Cross-Functional Collaborations: Experienced in partnering with data scientists, analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.
• Communication Skills: Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.
• Educational Background: Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field, with publications or contributions in recommendation systems being a plus.

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 video content and other services.

Benefits

• Great compensation package including salary plus performance bonus earning potential, paid annually.
• Flexible time off policies.
• Generous medical, dental, vision, STD, LTD, and life insurance.
• Health Savings Account (HSA) program.
• Health care and dependent care FSA.
• 401(k) plan, with employer match.
• Employer-paid commuter benefit.
• Support program for new parents.
• Pet insurance, and some offices are pet-friendly.

Pay

Actual pay will vary based on factors including, but not limited to, location, experience, and performance. The range listed is 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.

• Los Angeles, CA: $185,000—$225,000 USD
• San Francisco, CA: $205,000—$240,000 USD

Schedule

Hybrid schedule, in-office three days a week: Tuesday, Wednesday, Thursday.