What will you do? ------------------------ Solve problems in speech and NLP domain using advanced Deep learning and Machine Learning techniques. Few examples of the problems are - * Limited resource Speaker Diarization on mono-channel recordings in noisy environment. * Speech Enhancement to improve accuracy of downstream speech analytics tasks. * Automated Speech Recognition for accent heavy audio with a noisy background. * Speech analytic tasks, which include: emotions, empathy, keyword extraction. * Text analytic tasks, which include: topic modeling, entity and intent extraction, opinion mining, text classification, and sentiment detection on multilingual data. A typical day at work ----------------------------- You will work closely with the product team to own a business problem. You will then model the business problem into a Machine Learning problem. Next you will do literature review to identify approaches to solve the problem. Test these approaches, identify the best approach, add your own insights to improve the performance and ship that to production! What should you know? --------------------------------- * Solid understanding of Classical Machine Learning and Deep Learning concepts and algorithms. * Experience with literature review either in academia or industry. * Proficiency in at least one programming language such as Python, C, C++, Java, etc. * Proficiency in Machine Learning tools such as TensorFlow, Keras, Caffe, Torch/PyTorch or Theano. * Advanced degree in Computer Science, Electrical Engineering, Machine Learning, Mathematics, Statistics, Physics, or Computational Linguistics Why DeepAffects? -------------------------- * You’ll learn insanely fast here. * Esops and competitive compensation. * Opportunity and encouragement for publishing research at top conferences, paid trips to attend workshop and conferences where you have published. * Independent work, flexible timings and sense of ownership of your work. * Mentorship from distinguished researchers and professors.
Does the current state of media frustrate you? Do you want to change the way we consume news? Are you a kickass machine learning practitioner and aspiring entrepreneur, who has opinions on world affairs as well? If so, continue reading! We at UnFound are developing a product which simplifies complex and cluttered news into simple themes, removes bias by showing all (& often unheard of) perspectives, and produce crisp summaries- all with minimal human intervention! We are looking for passionate and experienced machine learning ENGINEER/INTERN, *preferably* with experience in NLP. We want someone who can take initiatives. If you need to be micro-managed, this is NOT the role for you. 1. Demonstrable background in machine learning, especially NLP, information retrieval, etc. 2. Hands on with popular data science frameworks- Python, Jupyter, TensorFlow, PyTorch. 3. Implementation ready background in deep learning techniques like word embeddings, CNN, RNN/LSTM, etc. 4. Experience with productionizing machine learning solutions, especially ML powered mobile/ web-apps/ BOTs. 5. Hands on experience on AWS, and other cloud platforms. GPU experience is strongly preferred. 6. Thorough understanding of back-end concepts, and databases (SQL, Postgres, NoSQL, etc.) 7. Good Kaggle (or similar) scores, MOOC (Udacity, Coursera, fast.ai, etc.) preferred.
Responsibilities : The Data Scientist will lead client-facing engagements aimed at solving clients most challenging business problems through the use of inspired analytics; the assembly and integration of disparate data sources, application of machine learning methods and impactful interpretation and communication of key insights through intuitive visualization and decision support tools. Desired Profile : - Strong fundamentals of machine learning, general statistics and data science principles - Experience with some of these methods: Regression, Decision Trees, CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Fuzzy Systems, Bayesian Belief Networks, Support Vector Machines, Ensemble Methods, Association Rules, Singular Value Decomposition, Principal Component Analysis, Clustering, Artificial Intelligence, Deep learning etc - Experience in some of these applications: Collaborative Filtering, Personalization, Consumer Segmentation, Text Analytics, Information Retrieval, Search Relevance - Solid data management and statistical modelling skills: SAS, R, Mahout, Matlab, Python (SciPy, NumPy), SQL and Excel - Strong problem solving and conceptual thinking, with ability to communicate even complex ideas in a succinct manner - Critical eye for the quality of data and strong desire to get it right - Ability to work in a fast-paced and deadline driven environment - Strong work ethics like sense of collaboration and ownership, result orientation, being team player - Candidate should be comfortable with working from clients- office Qualifications : - B.E./B.Tech from Tier 1 colleges (IIT/ISI/NIT/BITS/BIT/IIIT/REC) in Computer Science/Statistics/IT/ECE stream - M.S. or Ph.D. in Applied Mathematics, Statistics, Computer Science, Operations Research, Economics, or equivalent - Minimum 4+ years of relevant work experience in Data Science Requirement : - 4+ years of IT experience in data-driven or AI technology products - Hands-on expertise on analytical tools like R, SAS, Tableau, Excel. - Excellent communication, interpersonal and managerial skills - Ability to work with minimal supervision in a dynamic and timeline sensitive work environment - Team management experience is must - Work collaboratively with the Founders and Accounts Leads in terms of project execution and timelines. - Experience in decision science tools and techniques will be added advantage.
We are looking for Freelance online Data Scientist Trainers who can work with us part - time with the following skills: Experience using statistical computer languages (R, Python etc.) to manipulate data and draw insights from large data sets. Should have strong programming & Good applied statistics skills, such as distributions, statistical testing, regression, etc. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.Few examples are k-NN, Naive Bayes, SVM, Decision Forests,Random Forest ,Support vector machine,Principal component analysis. Experience using natural language processing techniques and Deep Learning using TensorFlow will be a plus. Should have minimum 5 years of relevant work experience.