Top Remote Machine Learning Engineer Jobs in Los Angeles, CA

As a Senior Machine Learning Engineer, you will develop and deploy machine learning solutions to enhance financial systems, improve user experience, and address fraud detection and other challenges.

The role involves building ML solutions for assessing cash flow risk, collaborating with teams on decision optimization, and utilizing diverse modeling techniques.

Design and implement AI solutions using cloud services, focusing on Generative AI and AI agent workflows, while managing MLOps practices and collaboration with teams.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

Lead the AI Engineering team to develop and implement AI-powered ML solutions, collaborate with stakeholders on strategic roadmaps, mentor team members, and ensure high-quality, scalable ML services.

Develop and execute vision for Pinterest's marketplace, improving ads delivery, conducting experiments, and collaborating across teams.

Design and deploy advanced AI capabilities for Zillow's AI Copilot, focusing on reasoning and decision-making systems in real estate.

As a Sr. Machine Learning Engineer, you'll develop ML solutions for healthcare, manage data pipelines, write production-ready software, and own ML services end-to-end.

This role involves building and managing AI/ML solutions for risk management, collaborating with teams, and providing technical leadership.

This role involves designing, developing, and scaling machine learning systems for payment flows and recommendations, leading technical initiatives, and optimizing complex financial decision systems.

Lead innovation in machine learning recommendations, mentor engineers, and collaborate with teams to enhance user experiences on Pinterest. Oversee large-scale ML systems and deliver strategic results.

The Senior Staff Machine Learning Engineer will develop AI-powered solutions, mentor engineers, and collaborate with cross-functional teams to enhance Airbnb's customer experience through advanced machine learning technologies.

The role involves developing machine learning solutions for autonomous vehicles, focusing on deep learning for prediction and planning, working collaboratively and researching innovative solutions.

As a Principal Machine Learning Engineer, you will lead AI-driven projects, build scalable ML pipelines, and collaborate cross-functionally to enhance healthcare services.

The Staff Machine Learning Engineer will design, develop, and deploy scalable ML algorithms, lead experimentation, and collaborate across teams to enhance AI solutions.

The Senior Machine Learning Engineer will design and implement machine learning architecture, develop models, and collaborate with teams to build data-driven features for a CRM product.

The Senior Machine Learning Engineer will enhance a platform for data scientists, lead ML service development, and collaborate cross-functionally to deliver AI solutions.

Develop and deploy AI models on edge devices, optimize ML models for real-time inference, and collaborate with firmware teams.

The Machine Learning Engineer will design, build, and operate data systems, optimizing data flows and integrating AI/ML models, mainly on AWS.

The Machine Learning Engineer will develop, deploy, and monitor ML solutions, collaborate with teams, and drive strategy using analytics.

As a Machine Learning Engineer, you will design systems for safe data ingestion and optimize data usage to enhance models and products, collaborating closely with the Product team and customers.

As a Machine Learning Engineer, you will focus on user-behavioral modeling, collaborate with teams, and engage in data processing and model deployment.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

Design and optimize AI infrastructure, ensuring reliability and efficiency. Lead projects, create ETL pipelines, and support ML workload operations.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.