Top Machine Learning Jobs in Los Angeles, CA

Lead the technical roadmap for the Ad Marketplace, design and optimize machine learning models, and collaborate with teams to meet objectives.

Analyze malware and detection tickets to improve detection capabilities. Collaborate with internal teams on threat detection inquiries and perform tasks to manage false positives.

As a Machine Learning Engineer, you'll build statistical models, optimize advertiser performance, design experiments, and collaborate across teams to enhance Liftoff's revenue growth.

The Director of Data & AI will lead strategies for data engineering, machine learning, and AI integration to enhance operations and automation for rocket manufacturing and launches.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

As a Staff Machine Learning Engineer, you will develop and maintain ML models for decision-making, optimize pipelines, and collaborate with a diverse engineering team.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

As a Machine Learning Engineer, you will design and optimize algorithms, manage ML data pipelines, and ensure system scalability while collaborating with teams to enhance software deployment.

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

The Machine Learning Engineer will build and deploy ML models, applying modern techniques to solve problems and collaborate with teams on ML-driven features.

Lead a multidisciplinary team of analytics engineers, data scientists, and machine learning engineers to develop and automate content launch processes while collaborating with cross-functional teams.

The role involves designing and maintaining machine learning models, analyzing data, and optimizing algorithms to solve business problems.

Lead the design and deployment of machine learning models to detect fraud, collaborating with teams to optimize performance and effectiveness while integrating solutions into existing systems.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

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

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.

Assist in developing AI-powered applications, support workflows, test APIs, optimize data pipelines, and collaborate with teams to build enterprise AI solutions.

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

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Lead modeling strategies for AI Bots in League of Legends by developing and implementing ML systems, collaborating with teams, and ensuring player experience enhancement through advanced ML methods.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

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

The Principal Software Engineer II will build and maintain machine learning components in Elasticsearch, collaborating with teams, writing scalable code, and owning projects from design to implementation.