Natural Language Processing (NLP) Engineer (Vice President)

Morgan Stanley Machine Learning (MSML) is Morgan Stanley's center of excellence responsible for working with business and IT teams across the firm to solve mission-critical problems. We are a highly motivated and collaborative team consisting of data scientists, machine learning engineers and members from academia. Our team is uniquely positioned to apply advanced AI and NLP to revenue generating business cases.

Responsibilities

- Independently work on end-to-end development of NLP models to derive insights from research publications, legal documents, regulatory requirements etc.

- Lead NLP projects and develop models in collaboration with members of MSML team, strats and quants

- Mentor junior members of the team

- Work with stakeholders to refine requirements and communicate progress

- Work with the team to develop a system for semantic search, knowledge graph creation, chat bot, summarization, 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

Qualifications Qualifications

Required

- 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 with good command over SemRegex

- 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

- 5-10 years of NLP experience

- MS in Computer Science with NLP specialization. PhD preferred.

Desired

- Reinforcement learning experience and it's application to NLP is highly desirable

- Deep Generative models and their application to NLP

- Research publications