Top Remote Machine Learning Engineer Jobs in Los Angeles, CA

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

Design and build AI-driven developer tools, integrate third-party AI models, mentor engineers, and improve AI coding agents to enhance software development processes.

Lead the development of AI/ML systems for TIDAL, enhancing user experience through personalized recommendations and playlists while collaborating with cross-functional teams.

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.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.

Dandy seeks a Machine Learning Engineer to develop 3D computer vision models using SOTA methods, collaborate with product teams, and implement MLOps pipelines.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Design and develop edge AI firmware for camera systems, ensuring accurate AI algorithms, collaborating on architecture, and mentoring engineers.

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 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.

As a Senior Machine Learning Engineer, you will design, build, and deploy large-scale ML systems to enhance Dropbox's AI features, collaborating with teams and mentoring peers.

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 Software Engineer III will focus on leveraging Generative AI for patient solutions, enhancing voice AI agents, and managing technical projects while mentoring peers.

Lead R&D to design and deploy ML models for conversational agents, enhance automation in customer support, and build scalable AI systems across business units.

Lead the development of advanced machine learning models and AI solutions for customer support, focusing on chatbot and voice automation technologies.

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.

The Senior Machine Learning Engineer will develop scalable ML systems, collaborate across teams to improve solutions, and manage critical ML infrastructure projects.

As an ML Engineer, you will design and manage ML pipelines, collaborate on privacy engineering, and implement MLOps practices, ensuring robust and scalable infrastructure.

The Machine Learning Engineer will create algorithms for automated processes, collaborate on data pipelines, analyze data sets, and improve machine learning solutions.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

Develop and implement large-scale machine learning models to enhance user ad predictions and better understand user interests through data mining and collaboration with product teams.

Design and build production-grade AI systems, combining ML and LLMs, ensuring performance and reliability while providing technical leadership and mentorship.