Machine Learning Engineer jobs in Los Angeles, CA

Lead the technical direction and architecture for agentic AI systems that process global trade data for real-time decision-making. Drive the full lifecycle of ML solutions, from ingestion and model training to observability and production deployment.

Lead the technical direction and architecture for agentic systems that process global trade data to provide real-time risk and compliance decisions. Build and maintain the end-to-end pipeline from data ingestion to model inference, while mentoring senior engineers and shaping the product roadmap.

Design, build, and operate production systems to detect and disrupt abusive behavior across the platform. Manage the end-to-end lifecycle of machine learning models, from prototype development to deployment and monitoring.

Design, implement, and scale machine learning models to protect users from harmful content and ensure regulatory compliance. Collaborate with cross-functional teams and leadership to set ML strategies and improve the organization's technical stack.

The role involves designing, training, and deploying large-scale models that power programmatic advertising and commerce media products, working within real-time bidding and pricing systems processing billions of daily events. Responsibilities include architecting high-performance models, productionizing scalable ML pipelines, extracting insights from massive datasets, and validating innovations through rigorous experimentation.

You will lead the technical direction and strategy for foundational machine learning capabilities, including visual representation learning and multimodal content understanding. This involves driving high-impact scientific initiatives from research through to productionization and cross-functional adoption.

The role involves developing generalizable tools and libraries to support machine learning projects and facilitating code reuse across the team. You will collaborate with data scientists to transition models from prototype to production while maintaining high standards for code quality and documentation.