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Machine Learning Engineer
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#238180
Remote / WFH
Job Description
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
• 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
