Top Remote Machine Learning Engineer Jobs in Los Angeles, CA

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 implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

As a Sr. AI/ML Engineer III, you will design and implement reinforcement learning algorithms, integrate them into simulation environments, and evaluate their performance. Collaborating with engineering teams, you will ensure the maintainability and transparency of AI components while communicating results and recommendations clearly.

Lead technical direction and execution of Lime's CX automation platform, building scalable backend services, decision engines, and human-in-the-loop workflows to automate rider issue resolution while enforcing fraud and trust guardrails and improving operational metrics.

Design, build, and maintain scalable AI/ML architectures; collaborate with data scientists, engineers, product, and compliance to integrate models; evaluate tools and processes; monitor performance and ensure industry-standard compliance and ethical practices.

The Azure AI/ML Engineer will design and implement AI solutions on Azure, focusing on automation, security, and compliance in collaboration with various teams.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will develop real-time streaming data pipelines for pricing algorithms and machine learning models, ensuring low-latency data delivery and system reliability. Responsibilities include collaborating with other teams, defining architectural standards, and mentoring junior engineers.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

Design, build, and scale data and ML systems; collaborate cross-functionally; implement data quality and governance frameworks; document data processes.

The Machine Learning Engineer will develop and integrate ML solutions, maintain ML systems, build data pipelines, and collaborate with cross-functional teams.

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.

The Staff AI/ML Engineer will lead AI product development, ensure system health, and collaborate with teams on product features while maintaining security and compliance.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As a Machine Learning Engineer, you'll evaluate neural network quality, coordinate with researchers, manage experiments, and report results to streamline AI software development.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

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

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

The Staff Machine Learning Engineer will develop AI/ML applications, collaborate with teams to implement models, and leverage a variety of technologies to enhance Twilio's customer support operations.