DevOps Engineer

Senior DevOps Engineer — AI/ML Infrastructure

Part-time | Remote

About OncoSwitch

OncoSwitch is a biotechnology startup developing short regulatory DNA switches designed to control where therapeutic genes are expressed. We combine AI-driven design with laboratory testing to advance selective gene expression in cancer cells.

We are looking for an experienced DevOps Engineer to help establish reliable computing infrastructure for our AI/ML and scientific workflows. You will work directly with our CTO and AI/ML team, turning research requirements into practical, secure and maintainable infrastructure.

What you will do

• Assess our infrastructure needs and recommend a practical setup across cloud, dedicated servers or a hybrid environment.
• Configure and maintain Linux-based compute environments, including GPU resources for model training and evaluation.
• Build reproducible development and research environments using containers and automation.
• Set up shared data storage, access controls, backups and recovery procedures.
• Establish monitoring, logging and resource usage tracking.
• Support CI/CD and infrastructure-as-code practices where they improve reliability and reduce manual work.
• Troubleshoot infrastructure issues that slow down the research team.
• Document the setup and provide clear operating procedures.

Initial priorities

Your first deliverables will be agreed with the CTO and will focus on:

• A prioritized infrastructure plan, including costs and dependencies.
• A working compute environment for agreed AI/ML workloads.
• Reliable storage, access management and tested backups.
• Reproducible environments and documentation the team can use independently.

What we are looking for

• Strong hands-on experience in DevOps, platform engineering or infrastructure engineering.
• Solid Linux administration, networking and troubleshooting skills.
• Practical experience with Docker and Python or Bash scripting.
• Experience deploying and maintaining cloud or dedicated-server infrastructure.
• An understanding of infrastructure security, monitoring and backup practices.
• The ability to work independently, prioritize essential work and explain technical trade-offs clearly.
• Professional working English for technical discussions and documentation.

Experience that would be a plus

• GPU infrastructure, NVIDIA drivers, CUDA environments or ML workloads.
• Infrastructure as code, such as Terraform or Ansible.
• Research computing, job scheduling or large scientific datasets.
• Supporting AI/ML teams in an early-stage company.

Previous biotechnology experience is welcome but not required.

Working arrangement

This is a remote, part-time role. Weekly hours, collaboration windows and compensation will be agreed based on experience, availability and the initial scope of work. Ongoing support expectations will be defined upfront to fit the part-time arrangement.

Why join us

You will help build the infrastructure behind an ambitious research programme at the intersection of AI, synthetic biology and gene therapy. Your work will directly improve how our scientists and engineers run experiments, manage data and develop models.

How to apply

Please submit your CV or LinkedIn profile and a short description of infrastructure you have personally built or maintained. Include any relevant GPU or AI/ML experience, your weekly availability, time zone and expected hourly or monthly rate.