Machine Learning Jobs in Anaheim, CA

The Senior Architect will lead software engineering projects, mentor teams, and help clients modernize their technology stack using innovative software solutions and AI-driven capabilities.

The Design Technology Lead will utilize computational design to drive data-informed decisions, mentor teams, and foster community in design technology initiatives.

The Director of Machine Learning will lead the development of ML models for audio, vision, and language applications, mentor the team, ensure project milestones are met, and collaborate with different stakeholders.

Lead the modeling strategy for ML Bots, developing predictive features, designing ML systems, mentoring engineers, and collaborating cross-discipline to enhance player experiences within games.

As Principal Software Engineer for the ML Platform team, you'll architect ML infrastructure supporting deployment, observability, and lifecycle management of models across Riot's games. Responsibilities include implementing CI/CD workflows, metric instrumentation, and ensuring a robust, extensible system for data scientists and product teams.

This internship involves working with machine learning concepts, algorithms, and applications while collaborating on projects and preprocessing data.

The Data Engineer will build and scale data systems and machine learning models, collaborate with team members, and enhance data pipelines and quality systems for Netflix's Knowledge Graph.

As an ML Applications Engineer, you will design and maintain software solutions, implement data workflows, optimize applications, and collaborate on usability enhancements.

Lead and mentor the Generative AI team, developing and optimizing machine learning models and solutions for multimodal data processing and document understanding.

Design and deploy deep learning models for autonomous rail vehicles, focusing on machine learning and computer vision challenges. Collaborate with cross-functional teams to integrate ML into real-world applications.

Lead design and development of scalable ML infrastructure for autonomous vehicles. Collaborate with ML teams for efficient model training and deployment. Manage end-to-end ML pipelines and cloud-based solutions.

The intern will assist in developing AI and machine learning systems, gaining hands-on experience with data processing, model training, and evaluation techniques.

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.

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.

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 an ML Engineering Intern, you will analyze stakeholder needs, research models, implement training loops, deploy models for texture generation, and evaluate model performance.

As a Graduate ML/Data Science Engineering Intern, you will analyze data, build ML models, and optimize video streaming performance to enhance user experiences at Xumo.

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.

Design and develop machine learning models and algorithms for advanced 3D printing systems, integrating with simulation frameworks and collaborating with software engineers.

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

Lead and build a new ML Platform team, align stakeholders, architect infrastructure for ML inference at scale, and ensure team execution on product delivery.