Top Remote Machine Learning Jobs in Los Angeles, CA

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

Lead and mentor a team of applied ML engineers at Cash App, focusing on building explainable ML systems to support decision-making across business teams.

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.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

Lead KYC modeling strategy, develop machine learning systems for customer onboarding and compliance, and oversee KYC monitoring and rules engine. Manage a team and align strategies with key stakeholders.

The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.

Manage and lead a team of Analysts, focusing on marketing measurement, optimizations, and utilizing machine learning to enhance campaign performance for clients.

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.

Lead the technical vision for Upstart's ML and simulations platform, modernizing infrastructure and mentoring a team while collaborating cross-functionally.

Lead the Applied Machine Learning team for Cash App, managing ML engineers, developing AI tools, and fostering collaboration on data-driven insights.

The Senior Machine Learning Engineer will build AI-driven customer support products, collaborate cross-functionally, and maintain large-scale ML systems, leveraging modern techniques for real-world impact.

Drive and lead complex machine learning projects, build and deploy models, analyze healthcare datasets, mentor teams, and conduct innovative research in AI/ML.

Lead AI/ML projects, develop machine learning models, mentor teams, and collaborate on innovative AI solutions for improving health outcomes.

The Director, AI/ML Engineering will lead high-impact ML projects, mentor teams, drive innovation, and collaborate on AI strategies to optimize health outcomes.

As a Senior AI/ML Software Engineer, you will design and implement advanced AI/ML systems for healthcare challenges, overseeing ML model performance and scalability while managing data pipelines and delivering insights.

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

The Senior Machine Learning Engineer at CDW will develop and deploy ML models, manage data pipelines, and collaborate with teams to solve business problems using AWS technologies.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

The Senior Machine Learning Engineer will design and optimize ML models, manage end-to-end ML projects, and enhance SailPoint's AI capabilities while collaborating with various teams to integrate AI features into products.

Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.

As a Staff Machine Learning Engineer, you will lead the design, implementation, and optimization of machine learning models, collaborate cross-functionally, and drive AI strategy to enhance SailPoint's identity security solutions.

Design and implement machine learning pipelines for fraud and payment systems, collaborating with data scientists and engineers to enhance reliability and decision-making.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Machine Learning Modeler will design and scale intelligent systems for data-driven decision-making, implementing ML pipelines, and collaborating with analytics teams for model production and insights.