Machine Learning Engineer, Rad AI

$150-178k

+ Equity

SQL

React

AWS

Docker

Kubernetes

TypeScript

GCP

JavaScript

Python

Postgres

Airflow

Terraform

Ansible

Azure

Grafana

Amplitude

PyTorch

Pulumi

Mid and Senior level

Remote from US

Generative AI for Radiologists

Open for applications

Generative AI for Radiologists

201-500 employees

HealthcareB2BArtificial IntelligenceScienceMedTech

Open for applications

$150-178k

+ Equity

SQL

React

AWS

Docker

Kubernetes

TypeScript

GCP

JavaScript

Python

Postgres

Airflow

Terraform

Ansible

Azure

Grafana

Amplitude

PyTorch

Pulumi

Mid and Senior level

Remote from US

201-500 employees

HealthcareB2BArtificial IntelligenceScienceMedTech

Company mission

To empower radiologists with AI — saving radiologists time, reducing burnout, and helping to improve the quality of patient care.

Job

Company

Role

Who you are

3+ years of industry experience in ML Engineering in cloud-native environments
In-depth knowledge of Python and Javascript/Typescript (preferable), or other modern languages in the ML domain
Experience with infrastructure and DevOps tools such as Kubernetes, Docker, and Ansible
Experience in distributed systems, storage systems, and databases
Strong knowledge of cloud computing platforms such as AWS (preferable), GCP, and Azure
Experience with monitoring, tracing, and logging tools such as Cloudwatch, NewRelic, Grafana, etc
Familiarity with infrastructure-as-code tools such as Terraform (preferable), Pulumi, Cloud Formation, etc
Excellent communication skills, with a strong sense of ownership and a systematic approach to problem-solving

What the job involves

We’re looking for a Machine Learning Engineer to join our MLOps team and help build and maintain the infrastructure that supports our cutting-edge AI research and products
In this role, you’ll develop tools and systems that accelerate language model R&D and serve those models to radiologists, ultimately improving clinical outcomes for patients
You’ll play a key role in implementing the infrastructure that connects our models to our customer-facing products
This role is backend-heavy but will include some fullstack development in both Python and Typescript
This is a unique opportunity to work at the intersection of AI and healthcare, shaping the future of how radiologists care for patients
Implement and maintain the infrastructure that supports our machine learning applications, services, and workflows
Build, maintain, and improve our ML platform that supports continuous integration, continuous delivery, and continuous training for our machine learning models
Develop fullstack, cloud-native services and serverless architectures to build scalable and resilient systems
Plan, design, and develop components in the data pipeline to enable various machine learning models in production
Write code that meets our internal standards for security, style, maintainability, and best practices for a high-scale HIPAA web environment
Deploy and maintain the full ML platform stack including monitoring and observability, data analytics, backend integration with customer-facing products, and the full model R&D lifecycle
Work with Product Management, Research, and Engineering to iterate on new features and address inefficiencies across our AI/ML infrastructure

Our take

Burnout seems to be reaching unprecedented and unsustainable levels amongst physicians, and radiologists are one of the most heavily impacted groups. A number of surveys have show that around 50% of them suffer from high workloads, which are exacerbated by outdated software and laborious work processes.

Rad AI, which was co-founded by the youngest radiologist in US history, is making serious inroads in alleviating these issues with AI. Its two main products are designed to save time: one by automatically generating impressions from dictated findings, and the other by automating patient follow-ups.

The company has been adding updates to its reporting software and is on a rapid growth trajectory, landing a number of respected radiology practices as customers and claiming industry awards. It has also secured major investment towards sustaining this momentum moving forwards, as more practices turn to AI to positively impact their patient care.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

40% employee growth in 12 months

Glassdoor (4.7)

Company

Funding (last 2 of 5 rounds)

May 2025

$8m

SERIES C

Jan 2025

$60m

SERIES C

Total funding: $147m

Company benefits

100% health, dental, & vision
Flexible PTO
WFH stipend
401k plan
Stock options
Socials & off-sites

Company HQ

Jackson Square, San Francisco, CA

Leadership

Doktor Gurson

(Co-Founder & CEO)

Co-founded and was CEO of portable smartphone charger startup Doblet (acquired by Alturki Holding). Has also founded a number of website hosting and migration companies. Is an Advisor to GoLinks, and BillionToOne.

Dr. Jeff Chang

(Co-Founder)

Youngest radiologist and second youngest doctor in US history, ER Radiologist at Greensboro Radiology. Was Co-founding CTO of Doblet. Has been an Advisor to medical device company Ikigai as well as a number of other startups.

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