Member of Technical Staff (MTS) Product: Backend & Infrastructure

Role Description

At Voio, we’re redefining how radiologists work. Today, medical imaging is slowed by fragmented tools — one system to view scans, another to dictate, and another to search patient context. We’re building a unified system that connects it all: fast, intelligent, and deeply intuitive.

At Voio, we’re redefining how radiologists work. Today, medical imaging is slowed by fragmented tools — one system to view scans, another to dictate, and another to search patient context. We’re building a unified system that connects it all: fast, intelligent, and deeply intuitive.

Our AI models originated from years of research at UC Berkeley and UCSF, but our mission goes far beyond the lab — we’re now building real-world systems that push the frontier of applied medical AI. Every line of code here helps doctors move faster, see clearer, and focus on care, not clicks.

We’re looking for a Backend Engineer who thrives in ambiguity, operates with ownership, and builds for scale. You’ll design and deploy the systems that power our AI-driven workflows — from data pipelines and inference services to integrations with PACS, RIS, and EMR systems.

• Design, build, and maintain backend services that power real-time medical AI applications.
• Develop robust APIs that connect radiology workflows — images, dictation, search, and structured reports — into one platform.
• Collaborate with ML, infrastructure, and clinical teams to bring multimodal models into production.
• Implement scalable data pipelines for imaging and clinical data.
• Drive architectural decisions that balance speed, safety, and long-term maintainability.
• Contribute to system design discussions and mentor teammates through code reviews and best practices.

• 4+ years of backend or distributed systems experience.
• Proficiency in Python, Go, or similar languages.
• Strong grounding in systems design, APIs, and data architecture.
• Experience with cloud infrastructure (AWS/GCP) and containerized environments (Docker, Kubernetes).
• Comfort working in fast, high-ownership environments where direction is minimal and impact is high.

• Familiarity with DICOM, HL7, or FHIR standards.
• Experience building or scaling production ML systems.
• Knowledge of data privacy, security, and compliance in healthcare setting

We hire for clarity, ownership, and judgment
.

• Thinks in systems. Sees beyond individual tasks to how everything connects.
• Executes with precision. Moves quickly without sacrificing long-term quality.
• Owns outcomes. Takes responsibility across design, build, and delivery.
• Builds with purpose. Writes code that improves lives, not just benchmarks.

You’ll work directly with leading engineers, clinicians, and researchers from UC Berkeley and UCSF — building products that didn’t exist before. If you want to shape how AI enters the clinic, and you care about craft as much as impact, this is your team.