31 results for Machine Learning Engineer Jobs in Los Angeles, CA, US

Design and implement scalable machine learning systems, collaborate on platform strategies, stay updated on ML technologies, improve organizational performance, and provide technical direction influencing the ML community.

Develop innovative machine learning technology and products, work on GenAI pipelines for image and video generation, deliver generative experiences on device, build augmented reality experiences using generative models, and collaborate with cross-functional teams.

Responsible for gathering requirements, developing data models and algorithms, supporting customer requests, writing tests for machine learning implementations, and collaborating with cross-functional teams to create and optimize data products.

About The Role & TeamOn any given day at Disney Entertainment and ESPN Product & Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming our media business for the future. Whether that’s evolving our streaming and digi...

Lead and manage machine learning projects, working on recommendation, classification, and optimization problems. Own the ML life-cycle, collaborate with engineers and researchers, and apply industry experience in frameworks like PyTorch and TensorFlow.

Responsible for deploying generative 3D models in cloud environments, optimizing inference pipelines for 3D model serving, developing scalable cloud architectures for real-time asset generation, integrating ML models into rendering pipelines, and implementing distributed training workflows for 3D mo...

Develops deep learning models for product features, conducts machine learning tests and experiments, participates in data collection planning, submits production code for model optimization, drafts technical patents, and publishes research. Requires proficiency in deep learning libraries and experie...

Responsible for developing and maintaining algorithms for personalization and recommendation systems, utilizing machine learning techniques. Collaborate with product and business teams to identify personalization opportunities and improve data processing through scalable ETL pipelines.

Lead the development and improvement of data-driven products in machine learning, focusing on NLP problems. Design and develop distributed systems, work with large datasets, collaborate with cross-functional teams, troubleshoot issues, and promote engineering best practices.

Hang is building the future of loyalty for brands.Hang is the next generation brand loyalty & membership platform. By harnessing the power of personalization, gamification, and its integrations ecosystem, Hang provides brands with a radically new type of loyalty experience for their customers.Today,...