Data Engineer- Machine Learning

San Francisco, CA 94107

Posted: 08/20/2018 Job Category: Engineering Job Number: 99803

Title:  Data Engineer- Machine Learning

Company: AI/ML  SaaS Platform- Medical Data

Location:  San Francisco, CA

Salary:  DOE

JBC is searching for brilliant Data Engineers, with machine learning experience,  to work on data products that drive the core business--a backend expert able to unify data, and build systems that scale from both an operational and an organizational perspective. Our client is on a mission to understand and structure the world’ s medical data using Machine Learning and Artificial Intelligence! 

As a Data Engineer you will:
  • Develop 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.
  • Build performant and expressive interfaces to the data
  • Build infrastructure to help not only scale up data ingest, but large-scale cloud-based machine learning

We’ re looking for Engineers who bring:
  • Experience building data pipelines from disparate sources
  • Hands-on experience building and scaling up compute clusters
  • Excitement 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.
  • A solid understanding of databases and large-scale data processing frameworks like Hadoop or Spark.
  • You’ ve not only worked with a variety of technologies, but know how to pick the right tool for the job.
  • A unique combination of creative and analytic skills capable of designing a system capable of pulling together, training, and testing dozens of data sources under a unified ontology.

Bonus points if you have experience with:
  • 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.

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