Senior ML Engineer - Recommendations & Personalization

Crunchyroll; San Francisco (CA); Hybrid; USD 185,000 - 240,000; Full time

Benefits offered by this job

Salary+bonus

Flexible time off

Medical/Dental/Vision

HSA

FSA

401(k) match

Commuter benefits

Parental support

Pet insurance

Job summary

Crunchyroll is seeking a Senior Machine Learning Engineer for Recommendation and Personalization. You will lead research, development, and testing of advanced models, working with product and engineering teams to deliver tailored experiences across anime ecosystems.

The role supports a hybrid schedule with offices in Los Angeles or San Francisco. You will collaborate with data scientists, engineers, and product owners to prototype innovative algorithms and deploy them into production.

Qualifications

• 8+ years hands-on experience in applied ML
• Proven track record building recommender/personalization systems
• Graduate degree in CS/ML or related field
• Experience collaborating with data scientists, engineers and product teams

Responsibilities

• Research, design, and implement ML algorithms for recommendation systems
• Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training and deployment
• Optimize models for accuracy, latency, and scalability
• Integrate personalization with other services and monitor model performance
• Collaborate on A/B testing and iterative improvements

Skills

ML experience

Recommendation systems

Python

TensorFlow

PyTorch

MLOps

AWS/GCP

Spark

Big data

Education

MS/PhD in CS/ML

Tools

MLflow

Docker

SageMaker/Databricks

Spark

Job description

Crunchyroll is seeking a Senior Machine Learning Engineer for Recommendation and Personalization. You will lead research, development, and testing of advanced models, working with product and engineering teams to deliver tailored experiences across anime ecosystems.

The role supports a hybrid schedule with offices in Los Angeles or San Francisco. You will collaborate with data scientists, engineers, and product owners to prototype innovative algorithms and deploy them into production.