Behavioral Signals

Machine Learning Engineer


Remote - Greece



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Job's description


Is machine learning and audio processing your passion? Can you work well in teams? Want to join a well funded and innovative startup? Then come join us at Behavioral Signals as a member of the ML team.

As a member of the ML Team, you will work on building supervised and semi-supervised models for emotion and behavior recognition from audio and speech signals. You will use and expand our existing pipelines and methodologies for continuously integrating vast amounts of speech data into our emotion and behavior estimation models. Based mostly on how something is being said (therefore using audio information) but also using information from what is being said (based on textual analytics) you will work along with our Core Product team on embedding the ML algorithms on various applications and demos, ranging from call center analytics to human-robot interaction and virtual assistants.

What you will do

  • Use existing and develop new methods for training models that predict the emotional states and speaking styles of a speaker based on what and how something is said.
  • Work on building algorithms for complex behavioral analytics in human interactions and discover high-level semantics such as empathy and humour.
  • Use and develop intelligent engineering workflows that continuously make use of huge amounts of annotated and weakly-annotated audio data, in order to build more robust models
  • Deploy robust and scalable deep learning models for speech analytics
  • Work closely with designers and product managers towards building new demos and products that help our clients benefit from our emotion and behavioral analytics

Please note that since our Engineering team is primarily located in Greece currently, this position is only open to people residing in UTC to UTC + 3 timezones.

Requirements

In order to be considered you must have:

  • Bachelor on computer science or related subject
  • Solid and demonstrable knowledge of ML principles: supervised learning, classifier evaluation / tuning, regression, clustering, deep neural nets, and active learning
  • Experience in building, reporting, communicating, deploying, and integrating machine learning methods to production
  • At least 2 years of experience with real-world machine learning problem solving
  • Excellent programming skills in Python
  • Experience with: pytorch, sklearn
  • Experience with one or more from audio analysis, speech recognition and/or text mining
  • Sense of ownership of your work
  • Ability to independently work on multi-domain projects and products


Extra credits will be given if you have one or more of the following:

  • Experience with MLOps tools for data and pipeline versioning, hyperparameter tuning, and experiment tracking and model serving, such as Kubeflow and Neptune
  • Experience in using Kubernetes, Docker, Flask, or other similar solutions for ML/DL model deployment
  • Postgraduate degree in machine learning, data science, or data mining

Benefits

  • Competitive salary package
  • Work from your favorite place
  • Work with highly-skilled engineers who enjoy autonomy, mentoring, and are aiming for exciting and challenging high goals
  • Flexible working hours




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