Senior Machine Learning Infrastructure Engineer

About the role

We’re seeking a Senior Machine Learning Infrastructure Engineer to join us in our mission to transform the discovery of therapeutics and materials.

As a member of the Machine Learning team, you’ll play a key role in building and maintaining the systems that put ML models and AI agents to work in drug discovery. LiveDesign ML trains and serves models on live project data, both in our own clusters and in customers' LiveDesign environments. Bunsen is an agentic platform where every session runs an AI agent in its own isolated Kubernetes pod. We also run locked-down environments for federated-learning collaborations with pharma partners.

You'll own the infrastructure behind these products, across our own clusters and customer clouds on GCP and AWS. Today, ML engineers handle it alongside feature work. You'll make it your focus: repeatable customer deployments, strong isolation for AI-generated code, and reliable, cost-efficient GPU systems.

Who will love this job:

- A Terraform or OpenTofu and Helm writer who has shipped with GitOps

- A solid Python and shell scripter

- A security-minded engineer who defaults to least privilege, managed secrets, and segmented networks

- A clear communicator who enjoys working closely with ML engineers and scientists

What you’ll do:

- Turn customer installs and upgrades into versioned, GitOps-driven releases (Helm, OpenTofu, Argo CD) with automated verification

- Design isolation for multi-tenant agent sandboxes: network policy, workload identity, runtime sandboxing, and egress control

- Secure CI/CD and the software supply chain with keyless auth, ephemeral runners, and pinned, signed images

- Build and operate locked-down partner environments with private networking, default-deny egress, just-in-time access, and audit logging

- Keep GPU-heavy training and inference reliable and cost-efficient, backed by observability, SLOs, and on-call

What you should have:

- At least six years of infrastructure, platform, or SRE experience

- In-depth understanding of Kubernetes operation (not just deployment)

- Robust background with GCP (and some familiarity with AWS)

We’d prefer to hire someone who has experience with:

- Running GPU workloads and model serving (vLLM, Knative) on Kubernetes

- Sandboxing untrusted code (gVisor, Kata Containers, Cilium)

- Shipping software into customer-owned or restricted-egress clouds

- Argo Workflows or batch/HPC scheduling

- Regulated environments (SOC 2, ISO 27001, GxP)

- Operating LLM or agent platforms

Pay and perks:

Schrödinger understands it’s people that make a company great. Because of this, we’re prepared to offer a competitive salary, equity-based compensation, and a wide range of benefits that include healthcare (with dental and vision), a 401k, pre-tax commuter benefits, a flexible work schedule, and a parental leave program. We have a company culture that is relaxed, but engaged, and over a month of paid vacation time. Our Office Management team also plans a myriad of fun company-wide events. New York is home to our largest office, but we have teams all over the world. Schrödinger is honored to have been included in Crain's New York Best Places to Work, BuiltIn's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces.