Top AI & Machine Learning Jobs in Los Angeles, CA

Build, deploy, and maintain machine learning models for Snapchat products. Apply ML techniques to ranking, recommendations, search, content understanding, image generation, and related applications. Contribute across data analysis, model training, evaluation, and production deployment while collaborating with cross-functional teams to launch scalable ML features and services. Use evolving AI tools and engineering practices while maintaining high standards for correctness, security, and production quality.

Lead product-focused quantitative analyses and machine learning efforts to generate actionable insights, drive product decisions, and optimize features. Collaborate with cross-functional teams to design metrics, build scalable statistical solutions, create dashboards, and communicate findings while using AI tools responsibly.

Perform quantitative analysis, data mining, and statistical modeling to generate actionable product and business insights. Design and track core metrics, build dashboards and visuals, collaborate with cross-functional teams, use AI tools to scale analyses, and drive projects to completion to inform product decisions.

Conduct research in user modeling and personalization, including graph modeling, generative recommendation, personalization, and ML efficiency. Lead research projects, build scalable prototypes, evaluate large-scale machine learning systems, and publish findings at top conferences. The role also involves mentoring interns and junior researchers and translating advanced research into product improvements.

Design and productionize causal machine learning models, including uplift modeling and treatment-effect estimation. Analyze A/B tests and quasi-experiments, develop experimentation strategies, evaluate modeling tradeoffs, and build scalable infrastructure. Collaborate with product and engineering teams, conduct code reviews, maintain engineering standards, communicate technical insights, and mentor others.

The Staff Machine Learning Engineer will lead the development of search ranking systems, focusing on machine learning models for relevance, quality, and personalization through various advanced techniques and collaboration with cross-functional teams.

Develop generative machine learning technologies and products serving millions of users. Build state-of-the-art image, video, language, and audio generation pipelines; deploy generative ML experiences on devices; create augmented reality experiences using generative and diffusion models; and collaborate with cross-functional teams to prototype new products.

Develop machine learning products and generative pipelines for image, video, language, and audio generation. Build on-device generative ML and augmented reality experiences using diffusion models, collaborate with cross-functional teams to prototype products, and solve open-ended technical problems. The role requires strong Python or C++ development, deep learning framework expertise, and research or engineering experience in generative or efficient models.

Lead technical strategy, architecture, and implementation for ML inference platform services. Design and scale distributed, high-throughput inference systems, collaborate across teams, drive availability, scalability, operational excellence, cost management, and provide company-wide technical direction and mentorship.

Product Manager for content ranking responsible for defining strategy, roadmaps, and metrics for content recommendation and ranking. Partner with engineering, data science, legal, and policy to launch scalable, privacy- and safety-minded content experiences, measure impact, and iterate on product improvements to drive engagement.