Teams at Schrödinger, Inc.

Own the infrastructure powering machine learning and AI agent platforms across company and customer cloud environments. Build GitOps-driven deployments, secure multi-tenant Kubernetes sandboxes, hardened CI/CD pipelines, restricted-egress partner environments, and reliable GPU training and inference systems. Collaborate with ML engineers and scientists while implementing observability, SLOs, cost controls, and on-call operations across GCP and AWS.

Leads enterprise application projects and serves as the technical authority for NetSuite and related business systems. Responsibilities include configuration, customization, integrations, workflow improvements, troubleshooting production issues, data-quality initiatives, technical standards, deployments, documentation, user training, and mentoring. Partners with technical and business teams to deliver scalable solutions across a polyglot cloud environment.

Manage AI and machine learning products for materials science, including customer demonstrations, roadmap planning, product expansion, ML model development, and leadership of the materials science ML team. The role requires deep expertise in materials science and ML, software-industry experience, customer engagement, public presentations, and global travel.