For ME/ M. Tech - 1 years post qualification relevant experience

• Candidate must have strong coding ability to write production quality code with relevant experience
• Object oriented analysis and design using common design patterns.
• Very strong scripting languages skills
• Design & development of large scale distributed systems in Python on Linux platform
• Design and maintain interfaces (REST) for integration with UI and other components & services
• Good knowledge in statistics and deep understanding on ML algorithms and their usage
• Knowledge of data analysis tools (for example: pandas), NLP tools (for example: spacy, stanford NLP, CoreNLP, NTLK, etc), Image Processing tools (for example: opencv), and Machine Learning tools (for example: scikit-learn etc.)
• Knowledge in any of the Deep Learning Frameworks like TensorFlow, Keras, PyTorch, RNN, CNN etc.
• Working experience in most of the common Machine Learning techniques related to Time series, Regression, Classification, Clustering, NLP, working with IoT data
• Knowledge in Crawling, Search Engine Optimization (SEO)
• Very strong data engineering skills [data parsing, web scraping, data transformation, data integration, etc.]
• Ability to parse from structured as well as structured data like html, word document, ecxel, csv, images (ocr), pdf, etc.
• Knowledge of regex, and data parsing/cleaning libraries (pandas, beautiful-soup, etc.)
• Knowledge of pySOLR/ElasticSearch-py/ELK Stack
• Nice to have understanding of big data related technologies and DevOps(Dockers, Singularity)
• Knowledge in Graph visualization database – Neo4J/Janus Graph or similar
• Ability to quickly script a working solution for a given problem
• Creative problem-solving skills
• A results-focused mindset Work closely with Product management team and other members of design team to execute solutions.
• Experience working with NLP/NLU based projects & technologies
• Knowledge in Machine Learning
• Knowledge in Crawling, Search Engine Optimization (SEO)
• Hands on Experience of Dockers, Kubernetes, Devops to be considered as added advantage

• Develop software solutions by studying information needs, conferring with users, studying systems flow, data usage and work processes, investigating problem areas, following the software development lifecycle
• Determines operational feasibility by evaluating analysis, problem definition, requirements, solution development, and proposed solutions.
• Identifying and analyzing user requirements
• Prioritizing, assigning and executing tasks throughout the software development life cycle