Top Machine Learning Engineer Jobs in Los Angeles, CA

The Machine Learning Engineer will design, develop, and implement advanced recommendation systems, collaborating with cross-functional teams to enhance personalization for a global audience.

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

The Senior Machine Learning Engineer will design, build, and deploy AI agents at scale, enhancing Dropbox Dash's search and organization features. Requires extensive ML experience and proficiency in Python and ML libraries.

The role involves developing ML models for search and recommendation, collaborating across teams, and managing data pipelines to optimize business objectives.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Lead technical strategy and architecture for machine learning systems, mentor engineers, and design scalable solutions for data mining and real-time inference.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

As a Machine Learning Engineer, you'll create and optimize production-ready ML solutions, manage the ML lifecycle, and conduct experiments.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The Senior AI/ML Engineer at Cooley will design, build, and maintain enterprise-scale AI/ML solutions across cloud platforms, optimize performance, and collaborate on AI implementations.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

Develop and maintain scalable AI/ML architectures, collaborate on integrating solutions into products, and ensure compliance with industry standards.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

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 Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Machine Learning Engineer will develop ML infrastructure, optimize models for anomaly detection, and manage technical projects to enhance space cybersecurity.

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

The role involves building, deploying, and maintaining ML infrastructure, optimizing systems, and ensuring production reliability while collaborating with data scientists and product teams.