Staff Machine Learning Infrastructure Engineer, Dyno Therapeutics

• We’re looking for a relentless systematizing infra expert who thrives at the intersection of machine learning and cloud-native engineering
• BS with 4 years+ of relevant industry experience
• Experience with cloud-native infrastructure (GCP or AWS), particularly for ML workflows
• Python fluency for scripting, automation, and infrastructure tooling
• Experience working in and managing containerized environments (Docker, Kubernetes)
• Hands-on experience supporting large-scale ML training and experimentation
• Ability to own vendor relationships from a technical perspective
• Alignment with Dyno’s core values - We seek individuals who step up when things get tough, recalibrate when priorities shift, and thrive in a high-expectation environment
• A proactive, problem-solving mindset

Desirable

• Staff ML Infrastructure Engineer
• This role is for someone eager to build the foundation underlying Dyno’s ML capabilities and help accelerate the discovery of next-generation gene therapies
• As Staff ML Infrastructure Engineer, you will be responsible for designing, optimizing, and scaling the infrastructure that powers Dyno’s ML-driven capsid design platform
• Your work will ensure our models train faster, deploy more efficiently, and operate reliably at scale
• This role is core to our platform’s success - enabling seamless iteration across ML research and engineering, and accelerating our mission to transform genetic medicine
• At Dyno, every role is mission-driven
• Whether in science, engineering, operations, or business, each AAViator contributes to solving some of the most complex challenges in genetic medicine
• Own and optimize ML compute infrastructure: manage dynamic allocation, track usage and costs, and forecast future needs
• Partner with other engineers to evolve our ML tooling and development environment, improving reproducibility, efficiency, and developer velocity
• Deploy ML models into production environments and improve inference performance
• Manage vendor relationships (e.g., Google Cloud, Weights & Biases), including technical oversight and future-looking decision making
• Work with urgency and adaptability, balancing innovation with execution
• Collaborate cross-functionally, leveraging Dyno’s high-trust, high-impact culture to drive results