AI/ML Job: Machine Learning/NLP Engineer


Machine Learning/NLP Engineer at Alpha

NYC, New York, United States 🇺🇸   (Posted Aug 1 2018)
About the company
Alpha's platform enables management teams at the world's leading organizations (Aetna, Citi, Experian, etc.) to make data-driven decisions about users, products, and markets.

Job position

Job description
Alpha is a venture-backed start-up based in New York, NY and our platform enables management teams to make data-driven decisions about users, products, and new markets.

At Alpha we are passionate about enabling teams to make data-driven decisions about users, products, and new markets. We believe the best path there involves more shots on goal – by vastly accelerating our clients’ abilities to learn we can help them build better products faster. We’re looking for a talented Machine Learning/NLP Engineer with a strong appreciation for simple, effective architecture and rapid experimentation. This position is full-time and on-site at our SoHo (NYC) office.


- Independently work on end-to-end development of NLP models to derive insights from text- Lead NLP projects and develop models in collaboration with team members

- Mentor less experienced members of the team

- Work with stakeholders to refine requirements and communicate progress

- Work with the team to develop a system for semantic search, entity recognition, knowledge graph creation, transcription, paraphrase detection, question answering etc.

- Train deep learning models with internal and external NLP datasets

- Deploy models to production and monitor performance

- Develop original ideas to create cognitive systems

- Participate in internal and external forums

Skills & requirements

- 3+ years of NLP experience

- MS in Computer Science with NLP specialization. PhD preferred

Helpful to have:

- Extensive experience in applying different NLP techniques to problems such as sentence summarization, question answering, sentiment analysis, knowledge extraction and conversational bots

- Expertise in NLP methods such as LSA, LDA, Semantic Hashing, Word2Vec, LSTM, BiDAF etc.

- Strong command over linear algebra and statistics having the ability to quickly translate ideas to efficient, elegant code

- Development experience in Python or Java/Scala with good command over respective data pipelining, matrix algebra and statistics libraries

- Stanford CoreNLP and other NLP tool kits

- Deep learning programming experience with Python/Tensorflow or similar library in a GPU environment

- Experience working with external reference datasets like SQUAD, SemEval, MSRP, WikTable, WikiQA, AllenAI etc.

- Tuning and optimization of sequential deep learning models

- Model deployment and scaling experience

Instructions how to apply
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