Komply.ai is looking for an NLP engineer to aid their mission in disrupting the legal space and changing how legal decisions are made. You will serve as the company’s internal subject matter expert on NLP, and its practical applications to deriving structured datasets from unstructured texts. You will apply your well-honed skills in the area of natural language processing to design, prototype, test, and deploy scalable data processing pipelines and systems consisting of multiple, interconnected NLP and other machine learning (ML) components. You will build these systems using both conventional and state-of-the-art algorithms and technologies, and guide us in building our NLP tech stack to support data-driven analytics products for the legal space.
You have excellent communication skills, with the ability to clearly articulate your work to technical and nontechnical people alike. You enjoy working with others in order to foster a friendly, collaborative and fun company atmosphere. You are able to think creatively and analytically, deliver practical and scalable solutions to complex problems, and understand when and where to make tradeoffs/compromises with minimal impact to the quality of your deliverables. And since we are an early stage startup, you will be wearing different hats at different times, and be eager to perform a variety of tasks.
This position reports directly to the head of the Data Science & Analytics team.
Our headquarters is located in Austin, TX. But we are also willing to consider remote candidates. If remote, you will be required to travel to the Austin headquarters at least 5 workdays per month.
What you will do:
• Design and build NLP pipelines that can scale with our products
• Contribute to the design and implementation of our data models
• Stay up to date on the cutting edge of NLP research to identify and leverage new techniques as appropriate
• Work with our legal subject matter experts to validate your approaches and results
• Work with our Product team to design back-end solutions which are aligned with front-end product requirements
• Work with other experts in the field to understand and validate other approaches.
You must have:
• M.S./Ph.D. in computer science, computational linguistics, data science, or a related discipline
• Experience designing, testing, and implementing NLP and general ML pipelines from scratch
• Demonstrable use of both conventional and advanced deep-learning (RNN, CNN, LSTM) based libraries in solving NLP problems; in particular, the extraction and structuring of data from text
• The ability to write neat, scalable, and reusable Python applications to accomplish the above
• Expertise in the areas of general NLP (text normalization, word vectors and embeddings, sentiment analysis, document classification, topic modeling, and entity extraction), natural language understanding (NLU), and creation and customization of domain-specific ontologies and knowledge graphs
• Experience with Python scientific libraries, including NLTK, spaCy, genism, AllenNLP, Keras, TensorFlow, PyTorch, scikit-learn, and numpy
• Experience working with relational database tools, such as Postgres, MySQL, AWS Redshift, and HP Vertica. Knowledge of graph databases (e.g., neo4j) is a big plus
• Experience working on processing news articles for summarization or knowledge extraction is another big plus.
Nice to have:
• Experience working in cloud computing environments such as AWS
• Experience with distributed computing frameworks such as Hadoop, Spark, Spark MLlib, and Spark-NLP
• Knowledge of micro-services and distributed architectures
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