Top Machine Learning Jobs in Los Angeles, CA

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.

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

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

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.

The Senior Machine Learning Engineer will build AI-driven customer support products, collaborate cross-functionally, and maintain large-scale ML systems, leveraging modern techniques for real-world impact.

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.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

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.

Lead KYC modeling strategy, develop machine learning systems for customer onboarding and compliance, and oversee KYC monitoring and rules engine. Manage a team and align strategies with key stakeholders.

The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.

The R&D Intern will develop and evaluate machine learning models, implement data processing pipelines, and collaborate with engineering teams on ML solutions for wireless communication.

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.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

Lead a machine learning engineering team to develop data-driven solutions for programmatic advertising, focusing on algorithms for bidding and ad optimization while collaborating across teams.

The Principal Machine Learning Engineer shapes the machine learning strategy and architecture, leads initiatives, mentors engineers, and influences technical decisions at SharkNinja.

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

As a Senior Machine Learning Engineer, you'll design and deploy ML models to prevent fraud, enhance safety, and support financial services at Block.

As a Staff Machine Learning Engineer, you will design and develop machine learning systems to prevent fraud, ensuring data quality and integrating diverse data sources while collaborating with cross-functional teams.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

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.