Natural Language Processing Engineer

Menlo Park, CA

Overview

Verantos (https://verantos.com) is a market leader in high accuracy real-world evidence (RWE) generation. The Verantos RWE platform integrates heterogenous real world data sources and generates evidence with the accuracy necessary for regulatory and reimbursement use. The Verantos RWE platform leverages data science and artificial intelligence along with advanced data sources such as electronic health records (EHR) to generate RWE capable of supporting complex clinical studies. Some of the largest biopharma companies in the world are Verantos customers.

We are looking for a natural language processing (NLP) engineer to join the AI team to scale up the AI components of Verantos’s solution. This position will be responsible for working with the Product Manager to drive the NLP strategy and building out all the NLP models and infrastructure.

The ideal candidate will be passionate about health care, software engineering, machine learning and stay up-to-date with the latest developments in the field.

Responsibilities

  • Understand business objectives and develop models that help to achieve them, along with metrics to track their progress

  • Articulate experiment plans that demonstrate the process of model building, refinement and productization

  • Manage available resources such as compute, data, and personnel so that deadlines are met

  • Analyze algorithms that could be used to solve a given problem and ranking them by their success probability

  • Explore and visualize data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world

  • Verify data quality, and/or ensure it via data cleaning

  • Supervise the data acquisition process if more data is needed

  • Find available datasets online that could be used for training

  • Define validation strategies

  • Define the preprocessing or feature engineering to be done on a given dataset

  • Define data augmentation strategies

  • Train models and tuning their hyperparameters

  • Analyze the errors of the model and design strategies to overcome them

  • Deploy models to production

  • Present model outcomes in a scientifically rigorous manner

Qualifications

  • Bachelor’s degree in engineering, math or science from a reputed institution (graduate degree strongly preferred)

  • 3+ years working as a NLP engineer

  • Proficiency with a deep learning framework such as TensorFlow

  • Experience building production-ready NLP systems, from preprocessing and normalization to monitoring model drift in a production environment, ideally using NLP libraries and technologies including Spacy, PyTorch & Deep Learning models

  • Proficiency in leveraging cloud-based machine learning resources such as those from Amazon Web Services or Google Cloud for model training and productization

  • Expertise in visualizing and manipulating big unstructured datasets