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.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
Skills Required
- At least six years of infrastructure, platform, or SRE experience
- In-depth understanding of Kubernetes operations
- Robust experience with Google Cloud Platform GCP
- Familiarity with Amazon Web Services AWS
- Experience with Terraform or OpenTofu, Helm, and GitOps
- Strong Python and shell scripting skills
- Experience running GPU workloads and model serving with vLLM or Knative on Kubernetes
- Experience sandboxing untrusted code with gVisor, Kata Containers, or Cilium
- Experience deploying software to customer-owned or restricted-egress cloud environments
- Experience with Argo Workflows or batch/HPC scheduling
- Experience in regulated environments such as SOC 2, ISO 27001, or GxP
- Experience operating LLM or agent platforms
Schrödinger, Inc. Compensation & Benefits Highlights
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Leave & Time Off Breadth — Time off is considered a standout, with over a month of paid vacation and two annual company shutdown weeks highlighted in official materials. This breadth is emphasized alongside a generally strong work-life balance proposition.
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Parental & Family Support — Family support is portrayed as robust, including paid parental leave, subsidized backup care for children, elders, and pets, and family‑planning resources. These programs are complemented by flexible work arrangements and caregiving resources described in corporate reports.
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Retirement Support — Retirement benefits are strengthened by a 401(k) plan with an employer match and additional protections like life and disability coverage. Company disclosures and third‑party summaries indicate these elements are core parts of the total rewards package.
Schrödinger, Inc. Insights
What We Do
Schrödinger is a leading provider of advanced molecular simulations and enterprise software solutions and services for pharmaceutical, biotechnology, and materials science research. The predictive power of Schrödinger's software allows scientists to accelerate their research and development, reduce research costs, and make novel discoveries.
Why Work With Us
We have a mission-driven culture that thrives off team collaboration. By utilizing a non-hierarchal approach, we hope to give all employees a voice and room to grow to their fullest potential. We actively engage in diversity and inclusion efforts, pay fairly, and always strive to provide a supportive atmosphere for our teams.
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Schrödinger, Inc. Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.