"Job Description:\nIf you have good programming skills, and want to solve complex real world problems using artificial intelligence, machine learning and computer vision while learning these on the job, READ ON.\nRun by IIT Kanpur alumni, AIMonk is a computer vision startup in stealth mode. We are building a uniquitous platform for computer vision using Artificial intelligence. \nWe are looking for an entry level(0-2 years of professional experience) programmer with deep interest in software engineering. This is a machine learning engineer position but there is no machine learning experience required. What we are looking for is sharp and curious brain who gets his/her high via solving problems.\nWilling to work in an early stage start-up, humility and is another skill-set required.\nCollege, pedigree doesn't matter but it is a good indicator of your skill-level. People who went to NIT, BITS are encouraged to apply. However, there is a programming challenge below. If you have the skills to solve that, it doesn't matter where you went to the college or what degree do you have.\n Be careful, if you work with us once, ordinary jobs will not interest you any more as they won't be challenging enough. Good thing, you will learn more than what you need to land those top 0.01% interesting jobs.\n\n\nJob Perks:\nOpportunity to work with the smartest people in the country on Artificial Intelligence and computer vision.\nLearning, tons of it.\nAutonomy, respect and freedom to set your own work-hours, opportunity to fail and learn.\nAnd of course! free beer and pizza once in a while.\n\nProblem statement: \nhttps://s3-ap-southeast-1.amazonaws.com/aimonk/SDE1-problem+statement.pdf"
"We are looking for Freelance online Data Scientist Trainers who can work with us part - time with the following skills:\n\nExperience using statistical computer languages (R, Python etc.) to manipulate data and draw\ninsights from large data sets.\nShould have strong programming & Good applied statistics skills, such as distributions, statistical\ntesting, regression, etc.\nKnowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial\nneural networks, etc.) and their real-world advantages/drawbacks.Few examples are k-NN, Naive\nBayes, SVM, Decision Forests,Random Forest ,Support vector machine,Principal component\nanalysis.\nExperience using natural language processing techniques and Deep Learning using TensorFlow\nwill be a plus.\nShould have minimum 5 years of relevant work experience."