ÍP AI/ML-Architect

JOB DUTIES AND RESPONSIBILITIES - Design, develop, and deliver AI/machine learning enabled solutions for specific industry problems. - Build scalable, available, and supportable processes to collect, manipulate, present, and analyze large datasets in a production environment - Articulate problem definition and work on all aspects of data including acquisition, exploration/visualization, feature engineering, and experimentation with machine learning algorithms, deploying models. - Develop working prototypes of algorithms and evaluate and compare metrics based on the real-world data sets - Provide design input specifications, requirements, and guidance to software engineers for algorithm implementation for solution/product development. MINIMUM REQUIRED KNOWLEDGE, SKILLS, AND ABILITIES: - 20 years of professional experience is required - Degree in applied math, statistics, machine learning or computer science. PhD/ MS is preferred - Deep understanding of statistics and experience with machine learning algorithms/techniques. - Proven programming skills, in particular C++ and Python, strong experience with DL frameworks such as Tensorflow, Theano and others - Scientific expertise and real-world experience in deep learning (convolutional neural networks, restricted Boltzmann machines, and deep neural networks) - Passion for solving challenging analytical problems - Ability to quickly qualitatively and quantitatively assess a problem - Ability to work productively with team members, identify and resolve tough issues in a collaborative manner. - Experience in applying machine learning techniques to real-world problems in a production environment BONUS KNOWLEDGE AND SKILLS: - Publications in the machine learning space is preferred - Articles on Advance topics in DL, including generating patents and research paper publications in IEEE and likes - Worked on large-scale, real-world problems in deep learning for a startup or large Enterprise - Open source contribution in algorithms, libraries and frameworks in DL - Membership of leading research groups in Deep learning area - Worked on Distributed computing environment such as Hadoop, Spark etc - Exposure to NoSQL technologies such as MongoDB, Cassandra - Impressive publication record in the top scientific journals. - Passion for data - Experience with participating and winning Hackathon/Kaggle like competitions in ML/DL areas