Senior Machine Learning Engineer, Recommendation and Personalization
About The Position
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 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, 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. This position can be based in our Los Angeles or San Francisco offices.
Requirements
- 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.
- 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.
- Experienced in partnering with data scientists and analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.
- Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.
- Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field.
Nice To Haves
- Publications or contributions in recommendation systems being a plus.
Responsibilities
- Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, and 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.
Benefits
- 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
- Pet insurance
- Some of our offices are pet friendly!
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What This Job Offers
Job Type
Full-time
Career Level
Senior
