S Senior Machine Learning Infrastructure Engineer Schrödinger · New York, NY, US Python Kubernetes LLM

ContentBuffer; New York (NY); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Healthcare (dental & vision)

401k

Pre-tax commuter benefits

Flexible work schedule

Parental leave

Paid vacation time

Company-wide events

Job summary

Schrödinger is hiring a Senior Machine Learning Infrastructure Engineer in New York to build and maintain the systems that run ML models and AI agents for drug discovery. You will own the infrastructure across our clusters and customer clouds on GCP and AWS, focusing on repeatable deployments, strong isolation, and cost-efficient GPU workloads.

You will work closely with ML engineers and scientists to design secure, scalable environments, implement GitOps-driven workflows, and ensure reliable,

Qualifications

• 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).

Responsibilities

• 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 environments, and trusted tooling.
• 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, with observability, SLOs, and on-call readiness.

Skills

Kubernetes operations

Python scripting

Shell scripting

GitOps workflows

Tools

GCP

AWS

Job description

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, ephemer
• 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.

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.

As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high degree of engagement, a commitment to working effectively in teams, and a passion for the company's mission. We place the highest value on creating a safe environment where our employees can grow and contribute, and refuse to discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, alienage or citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, sexual orientation, or any other protected characteristic. To us, \"diversity\" isn't just a buzzword, but an important element of our core principles and key business practices. We believe that diverse companies innovate better and think more creatively than homogenous ones because they take into account a wide range of viewpoints. For us, greater diversity doesn't mean better headlines or public images - it means increased adaptability and profitability.