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

Voio; Berkeley (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Voio is redefining radiology work by unifying imaging, dictation, and patient context into a single fast platform. We’re building backend systems that power AI-driven workflows for real-world clinical use.

As a Backend Engineer, you’ll design APIs, data pipelines, and services that connect PACS, RIS, and EMR tools while collaborating with ML and clinical teams to deploy scalable solutions in a healthcare setting.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Backend engineering

Distributed systems

Python

Go

APIs design

Data architecture

Cloud infrastructure

Docker

Kubernetes

High ownership

Education

Bachelor's degree in a technical field

Tools

Docker

Kubernetes

AWS

GCP

Job description

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.

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.

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.

Responsibilities

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.

What You’ll Do

• 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.

Qualifications & Requirements

• 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.

Desired Characteristics & Attributes

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

What We Offer

We hire for clarity, ownership, and judgment.

The Ideal Engineer

• 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.

Why Join Us

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.