B.S or M.S in Computer Science or Math(PHD in Data science + ML will be a plus)
5+ Years of experience in deep learning (extensive work on NLP is a plus)
10+ Years of industry experience
ML fundamentals: Data mining, wrangling, processing, visualization, model training, analysis.
Expertise in Designing and hands on with Coding
Software fundamentals: code + integrate models into production services.
Strong knowledge and skills in machine learning software development and architectures for machine learning (with focus on deep learning).
Research or Industry experience with one or more of following areas Natural Language Processing (NLP), Document Understanding, Information Retrieval, Natural Language Understanding.
Experience in building, deploying, and improving large scale Machine Learning models and algorithms in real-world products.
Proficiency in Python/C++ and deep learning frameworks e.g. Pytorch, Tensorflow.
Ability to synthesize the research literature, compare/contrast/critique and combine ideas into creating new ML models.
Published work in top-tier conferences & journals is a plus
Responsibilities
Build and refine machine learning models to solve NLP tasks and productizing the solutions at scale.
Staying abreast with the SOTA advancements and use them to formulate novel solutions.
Advancing the state of the art of NLP technologies for real world scenarios.
Developing novel machine learning and data mining algorithms
Contribute ideas and techniques to shape decisions and improve product quality metrics.
Participate in design, implementation and execution with a team of engineers, applied scientists and product managers.
Collaborate with Program Managers, Architects and stakeholders for workforce planning, demand planning and end-to-end solution design
Build, mentor, and lead a diverse high-performance team of Data Scientists
Create clarity, generate energy and deliver the impact
Ensuring compliance with Security, Privacy, GDPR etc. and performance criteria
Use data and insights from customer and production to contribute to some technical design and implementation decisions