Data Engineer - ML Infrastructure for Medical Imaging

Voio; Berkeley (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

Voio is redefining radiology workflows by unifying viewing, dictation, and patient context tools. Our team builds real-world AI systems with strong ties to UC Berkeley/UCSF research and clinical partners, delivering scalable data platforms for multimodal medical data and trusted, private AI applications.

You will shape data engineering and ML infrastructure, enabling fast, accurate model training and real-time inference across regulated healthcare environments.

Qualifications

• 4+ years of experience in data engineering, ML infrastructure, or distributed systems.
• Proficiency with Python and PyTorch, including model training/deployment workflows.
• Strong hands-on experience with NVIDIA Triton Inference Server and TensorRT.
• Familiarity with cloud environments (AWS, GCP) and containerized workflows (Docker, Kubernetes).

Responsibilities

• Design and maintain robust data pipelines to support large-scale medical imaging and multimodal datasets.
• Build scalable ETL systems for model training, validation, and deployment workflows.
• Develop data quality checks, lineage tracking, and observability across distributed systems.
• Benchmark and optimize model performance in production environments and identify bottlenecks.
• Collaborate with ML, infrastructure, and clinical teams to deliver reliable training environments.
• Deploy and manage GPU-based inference infrastructure using Triton and TensorRT for real-time AI applications.

Skills

Python

PyTorch

Data engineering

Distributed systems

NVIDIA Triton

TensorRT

AWS

GCP

Docker

Kubernetes

Tools

Docker

Kubernetes

NVIDIA Triton

Job description

Voio is redefining radiology workflows by unifying viewing, dictation, and patient context tools. Our team builds real-world AI systems with strong ties to UC Berkeley/UCSF research and clinical partners, delivering scalable data platforms for multimodal medical data and trusted, private AI applications.

You will shape data engineering and ML infrastructure, enabling fast, accurate model training and real-time inference across regulated healthcare environments.