Senior Machine Learning Infrastructure Engineer

Posted 34 Minutes Ago
Be an Early Applicant
New York, NY, USA
Hybrid
110K-160K Annually
Senior level
Healthtech • Machine Learning • Software • Biotech • Pharmaceutical
Opening new worlds for molecular discovery
The Role
Own the infrastructure powering machine learning and AI agent platforms across company and customer cloud environments. Build GitOps-driven deployments, secure multi-tenant Kubernetes sandboxes, hardened CI/CD pipelines, restricted-egress partner environments, and reliable GPU training and inference systems. Collaborate with ML engineers and scientists while implementing observability, SLOs, cost controls, and on-call operations across GCP and AWS.
Summary Generated by Built In

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. 
 
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 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.

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

  • 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.
  • 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.
  • 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.

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The Company
HQ: New York, NY
885 Employees
Year Founded: 1990

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

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Employees engage in a combination of remote and on-site work.

Typical time on-site: 2 days a week
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