Senior Software Engineer
Backend
Confirmed live in the last 24 hours
Fathom Health

51-200 employees

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

25%

1 year growth

78%

2 year growth

140%
Locations
New York, NY, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python NLTK
Data Structures & Algorithms
Apache Spark
Natural Language Processing (NLP)
Hadoop
Data Analysis
CategoriesNew
AI & Machine Learning
Software Engineering
Requirements
  • 5+ 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
  • A desire to collaborate in office 3 days weekly
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