Senior Machine Learning Infrastructure Engineer

Location: New York

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. Live Design ML trains and serves models on live project data, both in our own clusters and in customers' Live Design 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 Open Tofu and Helm writer who has shipped with GitOpsA solid Python and shell scripterA security-minded engineer who defaults to least privilege, managed secrets, and segmented networksA clear communicator who enjoys working closely with ML engineers and scientists

What you’ll do:

Turn customer installs and upgrades into versioned, Git Ops-driven releases (Helm, Open Tofu, 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

Payand 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, Built In's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces. Estimated base salary range: $110,000 - $160,000.

Actual compensation package is dependent on a number of factors, including, for example, experience, education, degrees held, market data, and business needs. If you have any questions regarding the compensation for this role, do not hesitate to reach out to a member of our Strategic Growth team. Sound exciting? Apply today and join us!

As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high…