Top Machine Learning Engineer Jobs in Los Angeles, CA

A Machine Learning Engineer will design and optimize AI components, develop datasets, evaluate models, and collaborate cross-functionally to enhance AI insights.

The role involves developing AI solutions, managing user behavior insights, and deploying large-scale AI services with collaborative efforts in a remote environment.

The Machine Learning Engineer will design, train, and evaluate computer vision models, collaborate on engineering improvements, and deploy ML systems for surgical workflows.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

Lead the design and deployment of scalable ML infrastructure, focusing on MLOps and LLM strategies, while mentoring team members and ensuring operational maturity.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

As a Machine Learning Engineer in Computer Vision, you'll develop AI solutions using advanced algorithms, focusing on image classification, segmentation, and video processing tools.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

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 Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The AI/ML Engineer will architect, maintain data pipelines, develop AI applications, and optimize distributed systems for fraud detection and prevention.

Implement and optimize production-ready analytics code, maintain Python repositories, research data sources, build predictive models, and collaborate with teams.

As a Junior AI/ML Engineer, you will work on generative AI applications, traditional ML projects, and MLOps, under the mentorship of senior engineers.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

Lead the Relevance team at Reddit to enhance search systems. Design large-scale systems for relevant search experiences, mentor engineers, and influence ML and Search strategies.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

As a Staff Machine Learning Engineer, you will design scalable ML systems, mentor engineers, solve complex problems, and optimize models in a fintech environment.

As a Machine Learning Engineer, you'll develop datasets and pipelines for navigation applications, work with geospatial data, build ML models, and ensure data quality.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

As a Machine Learning Engineer, you'll innovate features for dataset curation, model analysis, and integrations, focusing on Visual AI and open-source contributions.

The AI/ML Engineer will develop, deploy, and optimize machine learning models for grid stability and interconnection predictions, integrating data from various sources and collaborating with engineers.