Crunchyroll is growing and changing, presenting unique challenges and opportunities to support millions of anime fans around the world. The AI/ML team provides seamless help to our internal stakeholders, ensuring an exceptional experience for all Crunchyroll fans.
Requirements
- Strong expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Hands-on experience with Graph Neural Networks, GraphRAG, LLMs, Graph and Vector Databases.
- Experience with fraud analysis using machine learning, graph analytics, or NLP techniques.
- Proficiency in Python, R, or similar programming languages.
- Strong knowledge of cloud platforms (AWS preferred) and experience with data-related services (e.g., Databricks, SageMaker, Kinesis, Lambda).
- Ability to optimize AI/ML models for performance, efficiency, and cost-effectiveness.
Responsibilities
- Research, develop, and deploy Graph Neural Network (GNN) models, GraphRAG pipelines, and LLM-based solutions for real-world applications.
- Design and implement models across Crunchyroll domains leveraging machine learning, NLP, and graph-based techniques.
- Build and optimize interactive content discovery systems using Vector Databases and embedding-based techniques.
- Develop and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring.
- Work with AWS cloud services (e.g., SageMaker, Databricks, Lambda, S3, Kinesis) to scale AI/ML workflows.
- Optimize models for efficiency, performance, storage, and cost, ensuring they drive measurable business impact (e.g., content discovery, fraud prevention, payments, CDN).
- Collaborate with data engineering and software teams to ensure smooth deployment, monitoring, and scalability of AI/ML models in production.
Other
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
- 8+ years of experience in data science, with a strong focus on machine learning, AI, and production-grade model deployment.
- Strong analytical, problem-solving, and communication skills, with the ability to explain complex ML concepts to cross-functional stakeholders.
- 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.
