Top AI & Machine Learning Jobs

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps (tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams, perform model tuning and troubleshooting, and follow security and engineering standards.

Design, build, and deploy transformer-based and generative AI models into production. Implement training workflows, data pipelines, model serving, inference, and MLOps (tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams to translate requirements, troubleshoot production issues, and optimize model performance.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, feature engineering, training workflows, model serving, and MLOps practices. Collaborate with product and engineering teams, perform code reviews, monitor model performance, and support production troubleshooting and optimization.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, feature engineering, training workflows, model serving, and MLOps (tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams, perform code reviews, and troubleshoot and optimize production model performance.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, model serving, and implement MLOps practices. Collaborate with product, data, and engineering teams to operationalize models, monitor performance, troubleshoot issues, and follow software engineering standards.

Design, develop, and deploy transformer-based and generative AI models into production. Build data pipelines, feature engineering, and training workflows. Implement model serving, inference, monitoring, and MLOps practices. Collaborate with product, data, and engineering teams, participate in code reviews, troubleshoot production model performance, and continuously improve ML engineering practices.

Design, build, and deploy transformer-based and generative AI models; create data pipelines, feature engineering, training workflows; implement model serving and inference; apply MLOps best practices including versioning, testing, monitoring; collaborate with product and engineering teams; troubleshoot and optimize production AI systems.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product, data, and engineering teams to operationalize and monitor model performance.

Build and maintain large-scale analytics, ETL and reporting solutions for global pricing teams. Translate business requirements into data models, SQL/ETL processes and interactive dashboards (Tableau/Power BI/Domo). Cleanse and validate data, synthesize insights, present findings, and support repeatable modeling and reporting processes using SQL Server, Hadoop, and Python/R.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product and engineering teams, perform code reviews, monitor model performance, troubleshoot production issues, and continuously improve AI systems and technical skills.