Senior Software Engineer, Data

Fathom is on a mission to use AI to understand and structure the world’s medical data, starting with making sense of terabytes of clinician notes contained in 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. This process currently costs US hospitals over $15B annually and incurs 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 Senior Software Engineer, Data based remotely in North America to join our team and work on data products that drive the core of our business. We seek remote team members who are keen to learn how to build and support machine learning pipelines that scale not just in computational terms, but in ways that are flexible, iterative, and conducive to collaboration. If you are a data expert who can unify data and build systems that scale both operationally and organizationally, Fathom presents an intriguing opportunity. Your role and responsibilities will include: - Developing data infrastructure to ingest, sanitize, and normalize a broad range of medical data, such as electronic health records, journals, established medical ontologies, crowd-sourced labeling, and other human inputs. - Building efficient and expressive interfaces to the data. - Creating infrastructure to scale up data ingest and large-scale cloud-based machine learning. We are looking for a teammate with: - Five or more years of development experience in a company/production setting. - Experience building data pipelines from disparate sources. - Hands-on experience building and scaling up compute clusters. - 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, capable of designing a system that can compile, train, and test dozens of data sources under a unified ontology. Bonus points if you have: - Knowledge of developing systems to support machine learning, including experience working with NLP toolkits like Stanford CoreNLP, OpenNLP, and/or Python’s NLTK. - Expertise in managing healthcare data and/or complying with HIPAA. - Experience managing large-scale data labeling and acquisition, through tools such as Amazon Turk or DeepDive. Salary range: - $160,000 - $220,000 USD.