Linux Systems & Infrastructure Engineeremiologist

Company Description Miimansa focuses on addressing inefficiencies in the medical research-to-practice information flow, particularly those caused by high costs and the practical limitations of prospective clinical trials. The organization combines deep expertise in clinical data-management workflows, life sciences research, and artificial intelligence to build scalable, reliable research infrastructures. By designing robust “vasculature” for clinical research, Miimansa aims to streamline data-driven decision-making in healthcare. Team members collaborate across disciplines to advance evidence-based medicine and improve real-world care delivery.
About the role
We are looking for a hands-on Linux Systems & Infrastructure Engineer to support the computing and data-processing needs of our AI and research teams.
The role spans Ubuntu/Linux administration, on-premise and cloud infrastructure, GPU-enabled workstations, computational environments, and infrastructure automation. The ideal candidate is comfortable with the command line, independent troubleshooting, scripting, and practical problem-solving in a fast-moving startup.
You will work closely with technical and research teams to set up, maintain, monitor, and improve our computing infrastructure and supporting tools.
Key responsibilities
1. Linux systems and servers
Set up, configure, and maintain Ubuntu/Linux systems across on-premise and cloud environments.
Manage users, permissions, groups, storage, SSH access, and security controls.
Monitor system health, CPU, memory, GPU, and storage utilization.
Troubleshoot Linux, networking, hardware, and software issues, and maintain system documentation.
2. Data and compute environments
Set up and maintain Python environments, packages, dependencies, and tools for data processing and AI workloads.
Support researchers and engineers running large-scale data-processing and GPU workloads.
Automate routine administration, monitoring, and data-processing tasks using Bash, Python, or similar tools.
3. GPU and workstation infrastructure
Evaluate and recommend CPU, GPU, RAM, storage, networking, power, and cooling configurations for AI/ML and data-intensive workloads.
Support hardware procurement, installation, configuration, testing, and benchmarking.
Monitor compute resources and improve their utilization.
4. Resource monitoring and automation
Develop scripts and lightweight tools to track system health, resource utilization, and user activity.
Implement practical controls for shared computing resources and user access.
Automate monitoring reports and alerts where appropriate.
5. General infrastructure responsibilities
Take ownership of problems spanning hardware, software, networking, and infrastructure.
Establish practical IT and computing practices as the organization grows.
Work independently with evolving requirements, prioritizing simple, effective solutions.
Required skills
Strong practical experience administering Ubuntu/Linux systems and servers.
Comfortable with the Linux command line and independent troubleshooting.
Experience with Bash scripting; Python scripting is preferred.
Hands-on knowledge of Linux users, permissions, SSH, processes, services, storage, and networking.
Familiarity with Git and software environments and dependency management.
Understanding of CPU, RAM, GPU, storage, and networking hardware.
Experience setting up or maintaining servers, workstations, or compute environments.
Ability to develop scripts for routine administration, monitoring, and automation.
Desirable experience
NVIDIA GPUs, CUDA, and AI/ML compute infrastructure.
Docker and containerized workloads.
Cloud platforms such as AWS, Azure, or GCP.
Slurm or other workload and resource management systems.
Monitoring tools such as Prometheus and Grafana.
Networking and firewall configuration.
Ansible or other configuration-management tools.
Supporting data science, machine learning, or research computing environments.
What we value
A hands-on, resourceful approach and the ability to solve problems independently.
Willingness to work across hardware, Linux, networking, scripting, and applications.
A strong sense of ownership, without being constrained by narrow role boundaries.
Careful attention to security, access control, and data handling.
Comfort with ambiguity and changing priorities in a startup environment.
A preference for simple, reliable solutions over unnecessary complexity.

Work arrangement
No