Top Senior Level Machine Learning Jobs in Los Angeles, CA

Lead Machine Learning Engineer responsible for developing prediction and optimization engines for data platforms at Disney Entertainment & ESPN Technology. Drive innovation, develop novel solutions, and collaborate with cross-functional teams. Mentor team members and guide technical development.

Designs, develops, and programs methods, processes, and systems to analyze and generate insights from big data sources. Works with product and service teams to identify questions and issues for data analysis. Develops software programs and algorithms to evaluate large datasets. Interprets and communicates insights and findings to managers.

Lead Machine Learning Engineer responsible for developing and implementing analytical capabilities, machine learning models, personalization services, and data products/services for a healthcare marketplace. Collaborates with data scientists, mentors junior engineers, and addresses technical challenges for product development.

Design, build, and manage distributed services and pipelines for underwriting and credit at Cash App. Lead projects, maintain high code quality, collaborate with teams, solve technical problems, and mentor engineers.

Seeking a talented Machine Learning Engineer to join a leading online advertising agency in Los Angeles, focusing on innovative advertising technology. Responsibilities include designing data science programs, machine learning models, and architecture to support Generative AI. Must have practical experience with large datasets in web lead generation, search engine marketing, and cloud computing domains.

Lead a team of engineers to build one of Dropbox’s newest AI offerings, Dash. Foster operational excellence, streamline processes, and eliminate redundancies to ensure team agility. Provide strategic direction and contribute to technical and product strategies.

Seeking a Senior Machine Learning Engineer to drive product strategy forward by leveraging in-house code and data frameworks, developing scalable algorithms, and collaborating with cross-functional teams to enhance ML systems.