Top AI & Machine Learning Jobs

The AI Innovation Intern will develop AI-powered reports, automation tools, and internal applications, collaborating with multiple departments to improve workflows and operational efficiency.

The Data Scientist will develop predictive models and conduct complex analytics to support risk management strategies, collaborating with stakeholders and leveraging data.

The Associate Director, AI Engineering will lead the design and scaling of AI pipelines, manage stakeholder engagement, and ensure the ethical deployment of AI solutions within S&P Global.

Lead and inspire a small team in AI research focused on autonomy and knowledge capture related to semiconductor equipment. Responsible for project roadmap and development of software modules.

The Lead Machine Learning Scientist will develop and implement ML strategies to enhance marketing and product capabilities, identify opportunities for growth using data, lead core model development, and improve marketing spend efficiency through insights and experimentation.

The R&D Engineer Intern will design machine learning pipelines, translate research into products, and develop microservices for biomedical engineering applications.

As a Machine Learning Engineer II, you will design, implement, and optimize machine learning models and data pipelines, collaborate with teams, and maintain ML systems in production.

The AI Enablement Associate will implement AI solutions in portfolio companies, focusing on operational assessments, custom configurations, training, and building capabilities.

As an AI and Machine Learning Intern, you will provide software design support, develop AI/ML systems, analyze data trends, and create dashboards while ensuring project requirements and data accuracy.

Provide software design support for AI/ML systems and data analytics for projects, gathering information, design and deploying systems, and ensuring quality.

The Founding AI Engineer will design and build an AI-native compliance platform, handling complex financial data and developing scalable backend services, while establishing processes for enterprise readiness.