clustering jobs in San Diego

As an AI and Data Science Engineer III, you will translate business goals into machine learning use cases and model design approaches, perform exploratory data analysis to identify patterns and attribution opportunities, and apply clustering, sampling, feature transformation, and predictive modeling techniques. You'll build proofs of concept, validate solutions, and collaborate with clients and cross-functional analytics and data engineering teams throughout delivery.…See more The role requires 5+ years of industry experience applying data science or machine learning methods, with a bachelor's degree in a quantitative field such as engineering, mathematics, physics, machine learning, statistics, or computer science.

As an AI Science Intern, you will work alongside AI Scientists and Machine Learning Engineers to build, train, and evaluate machine learning and deep learning models on real-world datasets. Responsibilities include data gathering and ETL, feature engineering, model development using techniques like classification, regression, clustering, and neural networks, and designing experiments to measure impact.…See more You'll explore current AI/ML research including generative AI and LLMs, develop proofs-of-concept, and partner with cross-functional teams to translate insights into product features. The role requires strong Python and SQL skills, familiarity with core ML techniques and their mathematical foundations, and the ability to communicate findings to both technical and non-technical audiences.

As an AI and Data Science Engineer III, you will translate business goals into machine learning use cases and develop predictive models for marketing and advertising applications. You'll perform exploratory data analysis, apply clustering and feature transformation techniques, build proofs of concept, and validate solutions.…See more The role requires 5+ years of industry experience applying data science or machine learning methods, with a strong foundation in translating business requirements into model design approaches and collaborating across analytics and data engineering teams.

Staff Analytics Engineer responsible for designing and operationalizing agentic AI workflows, ML models, and Databricks applications at scale. Will build multi-step agent pipelines combining rules, ML models, and reasoning to solve complex business problems, then productionize them with monitoring, drift detection, and retraining strategies.…See more Requires 5+ years of hands-on ML engineering or data science with production system ownership, deep Python proficiency, strong traditional ML foundations, and proven Databricks expertise including notebook apps, dashboards, and ML pipelines. Will serve as technical authority, mentor peers, and influence architectural decisions across teams.