Senior Machine Learning Infrastructure Engineer

Job overview

The Senior Machine Learning Infrastructure Engineer role is listed in New York, NY; the posting describes the company's New York office as its largest but does not specify a work arrangement. The estimated annual base salary range is $110,000–$160,000. The role supports Schrödinger's Machine Learning team and its work applying models and AI agents to drug discovery. This engineer owns infrastructure for machine-learning products across company clusters and customer clouds. The role makes deployments repeatable, strengthens isolation and security for AI-agent environments, and improves the reliability and cost efficiency of GPU systems used for training and inference.

What you'll do

• Turn customer installations and upgrades into versioned GitOps-driven releases
• design isolation for multi-tenant agent sandboxes
• secure CI/CD and software supply chains
• build and operate restricted partner environments
• maintain reliable and cost-efficient GPU training and inference systems with observability and service-level objectives
• participate in on-call.

What we're looking for

Skills & competencies

new york ny

senior machine learning infrastructure engineer

machine learning

kubernetes

gcp

aws

terraform

gitops

gpu systems

ai agents

drug discovery

$110k–$160k/year

Work arrangement

• Weekend coverage required

Benefits & perks

• Healthcare including dental and vision, 401(k), pre-tax commuter benefits, flexible work schedule, parental leave, and more than a month of paid vacation.

Why this role

Requires at least six years of infrastructure, platform, or SRE experience, in-depth Kubernetes operations knowledge, and strong GCP experience with some AWS familiarity; on-call is part of the role.

About the employer

Schrdinger is hiring for this role. Industry: Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology). Sector: 54.