Machine Learning Jobs in Anaheim, CA

The Senior Manager, ML Engineering leads a team to productionize ML models, ensuring high performance and reliability while collaborating with various stakeholders.

The role involves developing ML pipelines for insurance tasks, fine-tuning models, and using NLP technologies to enhance automation in conversational AI.

Lead the ML strategy for Foundry at Adobe, overseeing the development of AI-native content and managing a team focused on generative media models.

As an ML Infrastructure Engineer, you will build infrastructure for AI development, automate ML workflows, and enhance developer experiences while collaborating with various engineering teams.

Design and optimize machine learning pipelines for large-scale systems, integrating models into user features and ensuring data integrity and performance.

Lead the design and optimization of ML systems at Scribd, managing cross-team projects, mentoring engineers, and shaping technical direction for ML initiatives.

Design and optimize machine learning systems, build scalable data pipelines, and run experiments to improve recommendations for Scribd's products.

The Staff Data Scientist will lead the design and development of Game Understanding Agents using machine learning methods, mentoring engineers and setting technical direction.

As a Machine Learning Engineer focused on computer vision, you will develop and deploy deep learning models, enhance production data pipelines, and collaborate with engineering teams to build impactful vision systems.

Lead the design and implementation of enterprise-scale AI/ML solutions on Azure and AWS, ensuring security, scalability, and performance. Collaborate with teams to optimize workloads and integrate solutions with data platforms.

The Principal Machine Learning Engineer will architect ML systems, lead development of data validation frameworks, and influence technical direction while mentoring engineers and ensuring high data quality standards.

Design and implement 3D machine learning models, process reality capture data, and integrate AI solutions in production environments for robotics applications.

The Senior Machine Learning Engineer will design and optimize ML discovery features, oversee projects, mentor engineers, and manage the ML lifecycle from data ingestion to model deployment.

Design and manage scalable ML infrastructures, develop cloud-based pipelines for multimodal datasets, and mentor junior engineers while overseeing ML operations.

As an AI/ML Engineer, you will develop multimodal models focusing on computer vision, video understanding, and agentic AI. Responsibilities include fine-tuning models, curating datasets, and building evaluation pipelines for efficient deployment.

The Senior Machine Learning Engineer will design and develop ML models for 3D assets, integrating AI into creator tools while collaborating with engineering and creative teams.

The Staff Software Engineer will architect and implement ML infrastructure, focusing on deployment, monitoring, and lifecycle management of ML models, applying MLOps practices.

Design, build, and optimize ML systems for recommendations at scale. Collaborate with teams on data pipelines, model development, and experimentation.

The role involves designing, building, and optimizing large-scale ML systems for personalized recommendations, focusing on data ingestion, model training, and collaboration with cross-functional teams.

This role involves developing and deploying large language models and generative AI systems, building scalable ML infrastructure, and mentoring junior engineers while collaborating with cross-functional teams.

The Machine Learning Engineer will develop and deploy ML models for personalized health programs, optimize recommendation systems, and establish best practices for ML lifecycle management.

The intern will research and implement ML models, deploy optimized image and 3D generation models, and evaluate performance while collaborating with the R&D team.

Interns will design, build, and deploy machine learning models that enhance Netflix's services, collaborating with various teams to translate business needs into ML solutions.

The Machine Learning Engineer will design and implement ML algorithms for wireless communication, analyze RF datasets, and integrate ML with Silvus' products.

The intern will conduct machine learning research, focusing on personalization, NLP, reinforcement learning, and computer vision while collaborating with various teams to improve Netflix's services.