Machine Learning/NLP Engineer
Alpha (alphahq.com) is a venture-backed and growth-stage company based in New York, NY whose on-demand insights platform empowers clients to rapidly validate growth opportunities. Our clients use Alpha to accelerate experimentation, inform business decisions with customer wants and needs, deliver and scale agile research capabilities, and develop better products faster. By integrating traditionally manual tasks like audience sourcing, concept designing, test scripting, and data reporting, the platform accelerates time-to-insight from months to hours.
In short, we’re the fastest way for organizations to learn more about their future customers.
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
- 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