Senior Machine Learning Engineer (Fraud Detection)

• In the role of senior machine learning engineer, 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
• In this Machine Learning Engineer role focused on Algorithm Development and End-to-End Production at our VOD streaming company, you will lead the creation and deployment of scalable ML models to detect account sharing fraud, drawing from user behavior data like geolocation, concurrent sessions, and device profiles
• This position is essential for collaborating with data scientists, product analysts, and data engineers, translating research prototypes into production systems that enhance detection accuracy while minimizing user disruption, aligning with proven strategies from streaming giants to boost subscriber growth
• 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 using 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 iteration to refine algorithms based on feedback and evolving evasion tactics

Benefits

• 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
• Generous medical, dental, vision, STD, LTD, and life insurance
• Employer paid commuter benefit
• Support program for new parents
• 401(k) plan, with employer match
• Health care and dependent care FSA
• Health Saving Account HSA program
• Pet insurance and some of our offices are pet friendly!- Education Background: Possess a master’s degree in computer science, machine learning, or a related quantitative field, with certifications in cloud ML being a plus
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders
• Experience: You bring 5+ years of hands-on experience in ML engineering, with a track record in fraud or anomaly detection systems, ideally in online, consumer facing products and services
• Cross-Functional Collaborations: Experienced in working with data scientists, engineers, and product teams to deploy models that support business goals like revenue optimization
• Communication Skills: Strong ability to document technical processes and explain algorithm decisions to diverse stakeholders for seamless integration
• Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or XGBoost, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks MLFlow, etc. Experience with cloud computing infra and tooling such as AWS/GCP
• Educational Background: Graduate degree (MS or PhD) in Computer Science, Statistics, or a related field