Software Engineer

Backend

Confirmed live in the last 24 hours

51-200 employees

Website

AI-powered autonomous medical coding for healthcare efficiency

Company Overview

Fathom is a pioneering company in the healthcare sector, utilizing advanced deep learning and natural language processing to autonomously code patient encounters, offering the highest automation rates and broadest specialty coverage in the industry. With the capacity to code millions of charts per day, Fathom can reduce coding operation costs by up to 50%, significantly shorten coding turnaround times, and provide on-demand coding capacity, all while ensuring patient information security. Backed by prominent investors and healthcare leaders, Fathom's technology is a testament to its industry leadership and commitment to enhancing efficiency in healthcare systems globally.

AI & Machine Learning

Company Stage

Series B

Total Funding

$65.9M

Founded

2017

Headquarters

San Francisco, California

Growth & Insights

Headcount

6 month growth

↑ 39%

1 year growth

↑ 85%

2 year growth

↑ 122%

Locations

Remote

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

Apache Spark

Data Analysis

Data Structures & Algorithms

Hadoop

Python NLTK

Natural Language Processing (NLP)

CategoriesNew

AI & Machine Learning

Software Engineering

Requirements

2+ years of software engineering experience in a company/production setting
Knowledge of algorithms, data structures and systems design
Experience building data pipelines from disparate sources
Hands-on experience building and scaling up compute clusters
A solid understanding of databases and large-scale data processing frameworks like Hadoop or Spark and the ability to evaluate which tools to use on the job
A unique combination of creative and analytic skills apt of designing a system capable of pulling together, training, and testing dozens of data sources under a unified ontology

Responsibilities

Developing data infrastructure to ingest, sanitize and normalize a broad range of medical data, such as electronics health records, journals, established medical ontologies, crowd-sourced labelling and other human inputs
Building performant and expressive interfaces to the data
Creating infrastructure to help us not only scale up data ingest, but large-scale cloud-based machine learning

Desired Qualifications

Know-how of developing systems to do or support machine learning, including experience working with NLP toolkits like Stanford CoreNLP, OpenNLP, and/or Python's NLTK
Expertise with wrangling healthcare data and/or HIPAA
Experience with managing large-scale data labelling and acquisition, through tools such as through Amazon Turk or DeepDive

Fathom is on a mission to use AI to understand and structure the world’s medical data, starting by making sense of the terabytes of clinician notes contained within the electronic health records of the world’s largest health systems. Our deep learning engine automates the translation of patient records into the billing codes used for healthcare provider reimbursement, a process today that costs hospitals in the US $15B+ annually and tens of billions more in errors and denied claims. We are a venture-backed company that completed a Series B round of financing for $46M in late 2022.

We are looking for a Software Engineer, Backend to work on data products that drive the core of our business. We want to work with teammates based remotely in North America, who are excited about learning how to build and support machine learning pipelines that scale not just computationally, but in ways that are flexible, iterative, and geared for collaboration. If you are a backend expert able to unify data, and build systems that scale from both an operational and an organizational perspective, Fathom is an opportunity worth exploring!

Your role and responsibilities will include:

Developing data infrastructure to ingest, sanitize and normalize a broad range of medical data, such as electronics health records, journals, established medical ontologies, crowd-sourced labelling and other human inputs
Building performant and expressive interfaces to the data
Creating infrastructure to help us not only scale up data ingest, but large-scale cloud-based machine learning

We are looking for a teammate with:

2+ years of software engineering experience in a company/production setting
Knowledge of algorithms, data structures and systems design
Experience building data pipelines from disparate sources
Hands-on experience building and scaling up compute clusters
A solid understanding of databases and large-scale data processing frameworks like Hadoop or Spark and the ability to evaluate which tools to use on the job
A unique combination of creative and analytic skills apt of designing a system capable of pulling together, training, and testing dozens of data sources under a unified ontology

Bonus points if you have:

Know-how of developing systems to do or support machine learning, including experience working with NLP toolkits like Stanford CoreNLP, OpenNLP, and/or Python’s NLTK
Expertise with wrangling healthcare data and/or HIPAA
Experience with managing large-scale data labelling and acquisition, through tools such as through Amazon Turk or DeepDive

Salary range:

$100 000 - $175 000 USD