Senior Research Scientist, Voice Program (NLU)
Position Details
- Lead research projects
- Lead scientific discussion with other research scientists to develop novel algorithms and initiatives that will support the vast amount of business data and resources
- Define short/middle-term direction of projects while aligning with business, product and engineering team
- Work with Project Management team to gather business requirements, define suitable KPIs and guide members on how to validate if the solution(s) built meets/exceeds the requirements/KPIs
- Support engineering teams and product teams to build large-scale, integrated speech processing systems, using both in-house developed solutions and external vendor solutions.
- Support junior-level research scientists
- Contribute to the advancement of science via writing papers, attending conferences and submitting patent proposals
Mandatory Qualifications:
- Doctoral degree in Computer Science, Machine Learning, NLP or related areas with 2+ years of industry experience.
- Strong background and hands-on experience in NLP/NLU/NLG or other areas related to conversational AI. Specifically, experience of working with one or more of these areas –text embeddings, semantic text matching, entity extraction / disambiguation, intent classification, question-answering, chatbots, text summarization, multi-turn dialog management –is expected.
- Familiarity with open-source ML, DL, NLP software. E.g. Python libraries like Scikit-learn, Tensorflow, Pytorch, and others.
- Strong programming skills in any programming language, preferably Python.
- Strong background in data structures and algorithms.
- Academic publications in top-tier peer reviewed conferences / journals such as ACL, AAAI, IJCAI, EMNLP, NeurIPS, ICML, ICDM, CIKM, KDD or others.
- English fluency and ability to communicate effectively with researchers, engineers and business people
- Self-motivated and willingness to take challenges to new technologies, research problems and services
Desired Qualifications:
- Practical knowledge of deep learning (DL)-based pretrained neural language models such as BERT, Universal Sentence Encoder or others and experience with pretraining / fine-tuning these models for downstream tasks.
- Knowledge of training large-scale ML/DL models on CPU/GPU-based hardware. Experience with distributed training
- Experience with end-to-end product development.
- Familiarity with DevOps, cloud-related development , and other related development toolkits.
- Passion for contributing to business by applying innovative solutions to real world problem
- 2+ years of experience leading a team of scientists