Senior Machine Learning Infrastructure Engineer
Schrödinger
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This role on the market
2,516 open infrastructure roles across 347 companies are on ApplySarthi right now, most of them in Bengaluru (141), Hyderabad (26), Delhi NCR (13).
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What infrastructure roles keep asking for: AWS (30%), Python (30%), Observability (25%), Kubernetes (24%), System design (24%), Linux (20%), Terraform (19%), CI/CD (17%) — counted across their open postings here.
AWS jobs · CI/CD jobs · GCP jobs · Kubernetes jobs
Schrödinger has 39 open roles listed here.
- Computational Materials Science, Formulations
- Computational Materials Scientist, Atomic Layer Processing and Chemical Reactivity
- Computational Chemist
- Computational Chemist, Target Druggability and Structure-Based Design
- Facilities Partner I - Hyderabad hyderabad
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for infrastructure roles keep coming back to AWS, Python, Observability, Kubernetes. Practise those questions before you sit with Schrödinger.
Questions you are likely to be asked
- Why do you want to join Schrödinger?
- What is your experience with Kubernetes? Tell me one thing you learned the hard way.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Senior Machine Learning Infrastructure Engineer at Schrödinger interview free →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
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Listed on greenhouse · posted 2026-11-04. ApplySarthi collects openings and links to application pages; the role is advertised by Schrödinger, not by us.