Top Machine Learning Engineer Jobs in Los Angeles, CA

The Machine Learning Engineer will build and deploy ML models, applying modern techniques to solve problems and collaborate with teams on ML-driven features.

The Staff Machine Learning Engineer will lead technical direction for ML technologies, design impactful ML solutions, mentor engineers, and drive cross-team initiatives.

Lead end-to-end machine learning projects, build models, perform analysis of healthcare data, mentor team members, and present findings to leadership.

Lead the technical roadmap for the Ad Marketplace, design and optimize machine learning models, and collaborate with teams to meet objectives.

Lead the design and deployment of machine learning models for personalized navigation, collaborate across teams, and drive technical excellence in ML practices.

Lead the vision for generative recommendations at Snap, designing and building generative models to enhance content discovery, personalization, and user engagement, while driving innovation and technical initiatives in the enterprise.

The Principal Machine Learning Engineer will drive technical roadmaps, optimize video recommendation systems, lead technical initiatives, and collaborate on machine learning strategies with cross-functional teams, ensuring scalability and performance.

Develop and deploy machine learning models for risk assessment, collaborating with teams to enhance Gusto's product offerings while ensuring model performance and reliability.

Design and maintain ML pipelines, build data ingestion tools, collaborate with data teams, ensure data quality, and solve technical challenges in a fast-paced environment.

Develop machine learning models to detect and reduce fraud within Block's ecosystems, while collaborating with various teams to implement solutions.

As a Staff Machine Learning Engineer, you will design and develop machine learning systems to prevent fraud, ensuring data quality and integrating diverse data sources while collaborating with cross-functional teams.

The role involves building machine learning models to detect risky activities, collaborating with cross-functional teams, and enhancing modeling capabilities. Candidates should have extensive experience in machine learning and strong analytical skills.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

Lead the design and implementation of AI/ML models for risk and fraud detection at Coinbase. Collaborate with teams to develop scalable systems, mentor engineers, and ensure effective AI/ML solutions align with company goals.

Lead strategic AI and ML initiatives for Tidal by developing personalization systems and collaborating with cross-functional teams. Responsible for technical leadership and system architecture.

As a Staff Machine Learning Engineer, you will develop and maintain ML models for decision-making, optimize pipelines, and collaborate with a diverse engineering team.

Develop machine learning models to prevent risky or abusive activities in financial transactions, ensuring a secure user experience for families using Cash App.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.