2+ Neural networks Jobs in Delhi, NCR and Gurgaon | Neural networks Job openings in Delhi, NCR and Gurgaon

Company Profile : Precily AI is a startup headquartered in Delhi NCR. Precily is currently working with leading consulting & law firms, research firms & technology companies. Aura (Precily AI) is a data- analysis platform for enterprises that increase the efficiency of the workforce by providing AI- based solutions. Responsibilities & Skills Required : The role requires deep knowledge in designing, planning, testing and deploying analytics solutions including the following : 1) Natural Language Processing (NLP), Neural Networks, Text Clustering, Topic Modelling, Information Extraction, Information Retrieval, Deep learning, Machine learning, cognitive science, and analytics. 2) Proven experience implementing and deploying advanced AI solutions using R/Python. 3) Apply machine learning algorithms, statistical data analysis, text clustering, summarization, extracting insights from multiple data points. 4) Excellent understanding of Analytics concepts and methodologies including machine learning (unsupervised and supervised). 5) Hand on in handling large amounts of structured and unstructured data. 6) The measure, interpret and derive learning from results of the analysis that will lead to improvements document processing. Skills Required : 1) Python, R, NLP, NLG, Machine Learning, Deep Learning & Neural Networks 2) Word Vectorizers 3) Word Embeddings ( word2vec & GloVe ) 4) RNN ( CNN vs RNN ) 5) LSTM & GRU ( LSTM vs GRU ) 6) Pretrained Embeddings ( Implementation in RNN ) 7) Unsupervised Learning 8) Supervised Learning 9) Deep Neural Networks 10) Framework: Keras/Tensor flow 11) Keras Embedding Layer output

• Experience with Big Data, Neural network (deep learning), and reinforcement learning • Ability to design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning applications according to requirements • Select appropriate datasets and data representation methods • Run machine learning tests and experiments • Perform statistical analysis and fine-tuning using test results • Extend existing ML libraries and frameworks • Keep abreast of developments in the field • Understanding of data structures, data modeling and software architecture • Deep knowledge of math, probability, statistics and algorithms • Ability to write robust code in Python, Java and R Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)