Senior Software Engineer (Backend/Data) San Francisco - USA

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 Senior Software Engineer (Backend/Data) to work on data products that drive the core of our business. We want to work with teammates in the Bay area, 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 electronic health records, journals, established medical ontologies, crowd-sourced labeling 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: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 at 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 labeling and acquisition, through tools such as Amazon Turk or DeepDive.Compensation:Company EquityPTO and Uncapped Sick Days401k Matching$1,500 USD Home Office BudgetVirtual and Local Office (San Francisco, New York City and Toronto) Team Building Events

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