Deep Learning Scientist
Affectiva is an MIT Media Lab spin-off focused on understanding human emotion. Our vision is that technology needs the ability to sense, adapt and respond to not just commands but also non-verbal signals. We are building artificial emotional intelligence (Emotion AI).
As you can imagine, such an ambitious vision takes a great team with a strong desire to explore and innovate. We are growing our team to improve and expand our core technologies and help solve many unique and interesting problems focused around sensing, understanding and adapting to human emotion.
Our primary technology measures human emotion through sensing and analyzing facial expressions. This technology is already being used commercially in a number of different verticals and use cases, and has been released to the public in the form of SDKs so that developers around the world can begin to use it to create a new breed of apps, websites and experiences.
This position is on the Science team; the team tasked with creating and improving our emotion recognition technology. We’re a team of researchers with backgrounds in computer vision, machine learning and affective computing. The Science team does everything from initial prototyping of state-of-the art algorithms, innovate new algorithms and produce models which can be included in our cloud and mobile products.
As Affectiva continues to invest in deep learning research, we are looking for a deep learning researcher with experience in solving computer vision problems such as object detection, localization, and classification. Experience working on video (object tracking, action recognition) is a plus, as well as any experience working with the human face (face recognition, emotion estimation, multi-modal recognition).
We have a wide variety of interesting research areas we would like to pursue where the solutions will requiring innovating on the current state of the art. Great candidates will be those who want to shape the future of this space, can execute ideas effectively and efficiently, and are passionate about emotion research.
- Run a multitude of deep learning experiments
- Prototype new ideas
- Explore a variety of approaches
- Refine promising ideas into product ready models
- Explore new methods to leverage Affectiva’s large dataset of spontaneous real-world audio-visual data
- Patent and publish findings in computer vision and affective computing conferences
- At least 2 years of experience using deep learning techniques (CNN, RNN, LSTM) on computer vision tasks (object detection, classification, action recognition)
- PhD in the field of computer vision, or equivalent job related experience
- Experience working with deep learning frameworks (e.g. TensorFlow, Theano, Caffe) including implementing custom layers
- Passionate about innovation and pushing state of the art research
- Demonstrated experience (publications, projects) solving machine learning problem
- Experience working on the face is not required but is highly desirable (face detection, face recognition, expression recognition, face landmark tracking)
- Good presentation and communication skills
Back to top