Top Machine Learning Jobs in Los Angeles, CA

As a Staff Machine Learning Engineer, you'll lead the Content Ranking team in enhancing machine learning models for video recommendations, ensuring scalability, performance, and technical direction across teams.

As a Staff Machine Learning Engineer, you will set the technical direction for the Ad Ranking team, design and deploy machine learning solutions, and mentor engineers while driving large cross-team initiatives.

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

Lead a team to build large-scale machine learning indexing and ranking systems while collaborating with product teams and enhancing team performance.

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'll build statistical models, optimize advertiser performance, design experiments, and collaborate across teams to enhance Liftoff's revenue growth.

The Principal Machine Learning Engineer will drive technical roadmaps, optimize video recommendation systems, lead technical initiatives, and collaborate on machine learning strategies with cross-functional teams, ensuring scalability and performance.

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

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.

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.

As a Senior Engineering Manager for ML & AI, you'll lead Data Science and ML initiatives, mentoring team members, and collaborating across R&D to drive strategic AI solutions that impact the business.

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.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

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.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

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 machine learning engineering team to develop ranking models. Manage project design, code reviews, collaborate with stakeholders, and ensure product scalability and quality.

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.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

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.