Senior Research Scientist - NLP
Washington DC
Kensho
Kensho develops cutting-edge products and technologies that transform businesses. We are the AI Innovation Hub for S&P Global.Kensho is a 100-person AI and machine learning company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions. Our toolkit illuminates insights by helping the world better understand, process, and leverage messy data. Specifically, our solutions largely involve natural language processing (NLP) and include speech recognition (ASR), entity linking (NED), structured document extraction, automated database linking, text classification, and more. We are continuously expanding our portfolio and are looking for passionate researchers to help us build and deploy state-of-the-art models across a variety of domains!
At Kensho, we believe in flexibility-first, and give our employees the opportunity to work from where they feel most productive and engaged (must be in the United States). We also value in-person collaboration, so there may be times when travel to one of our Kensho hubs (NY/DC/MA) will be required for team meetings or company events.
About The Role
Kensho is seeking a Senior Machine Learning Scientist to join our NLP Team, a product and research organization applying and extending the state of the art of textual and document-based AI across a variety of domains. The ideal candidate has deep industry or research experience and is a recognized expert in one or more core NLP fields, for example:
Named entity recognition (NER)Entity linking and coreference resolutionExtreme multiclass text classificationOpen-domain question answeringRelationship and fact extractionFinancial NLP
What You’ll Do
- Develop novel NLP algorithms and models using state-of-the-art techniques like deep learning and knowledge base-augmented ML
- Move the needle on unsolved problems in cross-domain NLP by conducting original research into replicating and augmenting human expert behavior with machine intelligence
- Write production-ready modeling code that can be scaled out to billions of documents and millions of users
- Contribute to a stellar engineering culture that values simplicity and function rooted in excellent design, documentation, testing, and code
- Collaborate with senior product and engineering leaders to identify the most promising problems to go after
- Share your results with your colleagues (presentations), senior executives (board meetings), and the world (published papers, patents, and blog posts)
- Mentor and lead other ML Scientists and Engineers to help make our team even more awesome!
Who You Are
-
Outstanding people come from all different backgrounds, and we’re always interested in meeting talented people! Therefore, we do not require any particular credential or experience. If our work seems exciting to you, and you feel that you could excel in this position, we’d love to hear from you.
- You hold a PhD or equivalent in Computer Science, Applied Math, or a similar field
- You have published in top-tier ML/NLP conferences (e.g., ACL, NAACL, EMNLP, NeurIPS, ICML)
- You have at least 4 years of experience performing novel research and deploying models to production in NLP or allied fields
- You have mastery of the techniques required to work effectively with real-world data and have developed a successful track record training ML models on large, messy datasets
- You have a deep understanding of what makes for well engineered software systems and understand that even superlative ML coupled with poor code will not go far
- You prefer to collaborate iteratively on hard problems with your teammates rather than spending stretches of time working alone and presenting your results intermittently
- You have a love for learning new skills and domains and share your knowledge freely, proactively, and effectively with others who are interested
- You are a generous and fun teammate and can take your work seriously without taking yourself too seriously
That said, most successful candidates will fit the following profile, which reflects both our technical needs and team culture:
Technologies We Love
- ML: Pytorch, NetworkX, Weights & Biases
- Deployment: Airflow, Docker, EC2, Kubernetes, AWS
- Datastores: Postgres, Elasticsearch, S3
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow AWS Classification Computer Science Data visualization Deep Learning Docker EC2 Elasticsearch EMNLP Engineering Excel ICML Kubernetes Machine intelligence Machine Learning ML models NeurIPS NLP PhD PostgreSQL PyTorch Research Testing
Perks/benefits: Career development Conferences Health care Medical leave Parental leave Pet friendly Startup environment Team events Unlimited paid time off
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