Founding Forward-Deployed ML Engineer

United States Digital Space LLC; United States; Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity stake

Job summary

United States Digital Space LLC is seeking a Founding Forward-Deployed ML Engineer to bridge research and clinical deployments. You will work on-site with hospital partners in Sunnyvale, CA, building evaluation workflows and integrating models into radiology pipelines.

The role emphasizes high ownership, cross-functional collaboration, and regulatory awareness, with visa sponsorship not available. Hybrid on-site work with travel required.

Qualifications

• Bachelor's degree in CS/Engineering/Math or related field, or equivalent practical experience.
• 2+ years of ML/Engineering experience.
• Experience with medical imaging workflows is appreciated.

Responsibilities

• Build reproducible evaluation pipelines for medical imaging AI in clinical settings.
• Lead on-site engagements with hospital partners to integrate models into workflows.
• Analyze model generalization, failure modes, and uncertainty for reliability assessments.
• Integrate ML models into clinical imaging systems (DICOM/PACS).
• Translate clinical needs into technical requirements and drive cross-functional projects to completion.
• Support regulatory submissions and clinical evaluations (FDA pathways).
• Ensure data privacy and HIPAA compliance across deployments.
• Establish and maintain MLOps for deployment and monitoring.

Skills

Medical imaging workflows

DICOM/PACS integration

MLOps

Python

Clinical deployments

Customer-facing

Education

Bachelor's degree in CS/Engineering/Math or related field

Tools

Docker

Kubernetes

AWS/GCP/Azure

Git

Job description

About the Role

This is a founding-team opportunity at a small, fast-moving healthtech AI company building evidence infrastructure for safety-critical medical imaging AI. As a Founding Forward-Deployed ML Engineer, you will sit at the intersection of research, product deployment, and clinical operations — working directly with hospital partners to evaluate and deploy medical imaging AI in real-world clinical settings.

You will play a central role in bridging the gap between benchmark performance and clinical reliability, translating AI models into trusted tools for patient care. This is a high-ownership, high-impact role suited to someone who is equally comfortable writing code, navigating clinical environments, and driving cross-functional projects to completion.

Work arrangement: Hybrid, on-site in Sunnyvale, CA. Travel to hospital partner sites required as needed.

Visa sponsorship: Not available.

What You'll Do

• Build reproducible evaluation pipelines and validation workflows for medical imaging AI in clinical settings.


• Lead forward-deployed engagements by working on-site with hospital partners to integrate models into clinical workflows.


• Analyze model generalization, failure modes, and uncertainty to inform clinical reliability assessments.


• Integrate ML models into clinical imaging systems and radiology pipelines (DICOM/PACS).


• Translate clinical needs into technical requirements and drive cross-functional projects through to completion.


• Support regulatory submissions and clinical evaluations (FDA pathways such as 510(k) and De Novo) and maintain related documentation.


• Ensure data privacy and regulatory compliance (HIPAA) across all ML deployments.


• Establish and maintain MLOps practices for deployment, monitoring, and ongoing evaluation.

What We're Looking For (Required)

• 2+ years of Machine Learning / Engineering experience.


• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.

Required Skills & Experience

• Hands-on expertise in medical imaging workflows and integration: DICOM/PACS, radiology pipelines, and integrating ML models into clinical systems.


• Practical MLOps and model evaluation skills: building reproducible evaluation pipelines, model validation/monitoring, and proficiency with Python and common ML frameworks (PyTorch / TensorFlow, Docker, Kubernetes).


• Hands-on experience deploying ML models to cloud platforms (AWS, GCP, or Azure) with containerized environments and ML-focused CI/CD pipelines.


• Experience navigating healthcare data privacy and regulatory compliance (HIPAA, FDA considerations) in ML deployments.


• Experience supporting regulatory submissions and clinical evaluation processes (e.g., preparing evidence for FDA 510(k) or De Novo pathways).


• Strong customer-facing skills: ability to communicate with clinical and industry partners, own engagements end-to-end, and drive cross-functional projects to completion.


• Willingness to travel to hospital sites and work on-site for customer deployments as needed.

Compensation & Benefits

Base salary: $150,000 – $230,000 USD annually, depending on experience.

• Early-stage equity opportunity as a founding team member.

Location

Sunnyvale, California, USA. Hybrid on-site role with travel to hospital partner sites as required. Remote work is not available for this position. Visa sponsorship is not offered.