Top AI & Machine Learning Jobs

As an AI Data Engineer, you will develop full stack applications integrating AI capabilities to support pharmaceutical research, enhancing workflows and productivity. Responsibilities include collaborating with researchers, developing scalable backend services, and deploying systems in AWS.

Develop, validate, and interpret ML models and end-to-end pipelines to predict oral drug absorption using large, heterogeneous biopharmaceutics and clinical datasets. Emphasize model explainability, uncertainty quantification, and mechanistic/physics-informed approaches, translate outputs into actionable insights for drug development teams, and communicate results via reports, presentations, and publications while contributing to AI-enabled predictive platforms.

Lead technical strategy and build scalable AI/ML platform infrastructure on AWS and Kubernetes. Design IaC, CI/CD, observability, security, and cost/capacity practices. Mentor engineers, improve deployment reliability, and enable generative AI workloads, model routing, and operational metrics across multiple environments and regions.

The Senior Manager will lead the AI for Targeting & Segmentation program, ensuring alignment with market needs, and oversee cross-functional delivery to realize business outcomes through AI capabilities.

This role involves developing AI and machine learning models for vaccine strain selection, integrating biological data, and validating models through rigorous benchmarking while collaborating with various scientific disciplines.

Responsible for designing and developing AI solutions for Oncology R&D, collaborating with scientists to translate complex questions into actionable insights, and contributing technical expertise in rapidly prototyping AI applications.

Lead the Oncology AI product strategy and roadmap, manage AI engineering teams, and drive stakeholder engagement for impactful AI solutions in R&D.

The role involves building AI-enabled solutions, developing data pipelines, and collaborating with teams to enhance Oncology R&D workflows.

Lead delivery of AI/ML models and analytics for a brand or therapeutic area, translate technical results into actionable commercial recommendations, collaborate across analytics, engineering, digital and commercial teams, ensure data ecosystem readiness, and communicate insights to stakeholders to drive strategy and tactics.

The internship focuses on applying AI in healthcare to improve patient outcomes and engage healthcare professionals, involving project work and learning opportunities.