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Ellation, Inc.

Senior Machine Learning Engineer, Fraud Detection

Ellation, Inc., Los Angeles, California, United States, 90079

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Senior Machine Learning Engineer, Fraud Detection

About Crunchyroll

Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We 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 – it’s powered by the anime content we all love. Join our team, and help us shape the future of anime! About the role

As a senior machine learning engineer, you will report to the director of data science and machine learning in the Center for Data and Insights and work from Los Angeles or San Francisco, California. In this role, focused on algorithm development and end‑to‑end production for our VOD streaming company, you will lead the creation and deployment of scalable ML models to detect account‑sharing fraud, using user‑behavior data such as geolocation, concurrent sessions, and device profiles. You will translate research prototypes into production systems that improve detection accuracy while minimizing user disruption and driving subscriber growth. Core Areas of Responsibility

Design and implement machine learning algorithms, including anomaly‑detection models, to identify unauthorized account sharing in real time. Develop end‑to‑end ML pipelines for data preprocessing, model training, evaluation, and deployment on cloud platforms. Optimize models for performance, scalability, and efficiency to handle high‑volume streaming data. Integrate ML solutions with existing systems via APIs and establish monitoring for model drift and retraining. Collaborate on A/B testing and iterate to refine algorithms based on feedback and evolving evasion tactics. About You

Experience:

5+ years of hands‑on ML engineering, with a track record in fraud or anomaly‑detection systems, ideally in online, consumer‑facing products and services. Technical Skills:

Expert in Python and frameworks such as TensorFlow, PyTorch, or XGBoost; proficiency with MLOps tools (MLflow, Docker) and cloud services (AWS SageMaker, Databricks, GCP). Cross‑Functional Collaboration:

Experience working with data scientists, engineers, and product teams to deploy models that support business goals such as revenue optimization. Communication Skills:

Ability to document technical processes and explain algorithm decisions to diverse stakeholders. Education:

Master’s degree in Computer Science, Machine Learning, or a related quantitative field; certifications in cloud ML are a plus. Additional:

Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non‑technical stakeholders. About the Team

Our team of passionate machine learning engineers and data scientists has already made a significant impact across product offerings, content strategy, and user engagement metrics. As we expand, the team will continue to be the cornerstone of innovation and growth across various business verticals. Why You Will Love Working at Crunchyroll

In addition to a fun, passionate, and inspired work environment, you will receive: Competitive compensation package including salary plus performance bonus potential. Flexible time‑off policies. Generous medical, dental, vision, STD, LTD, and life insurance. Health Savings Account (HSA) program. Health care and dependent care Flexible Spending Account (FSA). 401(k) plan with employer match. Support program for new parents. Pet insurance and pet‑friendly offices. Pay Range

$185,000 – $230,000 USD (actual pay varies by location, experience, and performance). Our Commitment to Diversity and Inclusion

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.

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