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# Infrastructure Engineer

- **Company:** Freeman Investment Company, L.P.
- **Location:** San Mateo, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Bash Shell, Cloud Computing, Python (Programming Language), Machine Learning, Software Engineering, Graphics Processing Unit (GPU), Google Cloud, Autoscaling, AI Platforms, Kubernetes, Deployment Automation, Terraform
- **Published:** July 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/software-engineer-core-infrastructure-san-mateo-ca--1f91bbe6-64e8-4cb0-9980-c3b6cc775221

## About the Role

* 5+ years of experience building and maintaining cloud infrastructure at scale, e.g. within AWS or GCP
 * Proficient with Python, Bash, Terraform, Ray and Kubernetes
 * Ideally, experience building and maintaining compute clusters running distributed ML training jobs with 1,000+ GPUs
 * Nice to have: hands-on experience with physical hardware + datacenter management, Amazon Web Services (AWS), Artificial Intelligence (AI), Automation, Autoscaling, Biology, Biotech and Pharmaceutical, Chemistry, Cloud Computing, Computational Chemistry, Drug Design, Drug Development, Drug Discovery, GCP (Good Clinical Practices), GPU (Graphics Processing Unit), Machine Learning, Medical Products, Physics, Problem Solving Skills, Resource Management, Simulation, Software Engineering

## Description

Genesis Molecular AI is building a world-class computational team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry. We are looking for an Infrastructure Engineer that is excited to help develop new medicines and play a critical role in building out our AI platform.

You Will

 * Work on our infrastructure team to maintain and grow our multi-cloud compute infrastructure that supports our ML model training, computational chemistry research, and ongoing drug discovery efforts
 * Build out our configuration and procedures for monitoring, resource allocation, and deployment automation, as we continue to grow our autoscaling compute clusters to handle larger workloads
 * Work on orchestration scheduling framework to increase our execution throughput, reliability, and compute utilization across heterogeneous pipelines


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