What makes you a great fit for this role
You're awesome at
- Dealing with large data sets
- Machine learning techniques and algorithms, such as k-NN, Naive Bayes, CART
- Quickly prototyping ideas/solutions and performing critical analysis and using creative approaches for solving complex problems.
You'll be improving & responsible for
- The key feature of the cradle is being responsive. The sensors in the cradle detect for early wake-up signals of the baby – twitch, notch, increased movement, activity, startle reflex, changes in breath rate.
- The cradle acts on these signals and if it is still sleeping time, rocks the baby to sleep along with soothing music. Through machine learning, the cradle creates personalized sleep recipes to help the baby sleep better.
- The cradle also learns patterns and identifies periods when a baby needs maximum attention and soothing. Provides related tips to parents to maintain a healthy sleep schedule.
- Restlessness monitor: Indication of an impending illness or cranky baby the next day if the baby had a restless night.
- Baby growth – Weight measurements from oscillations, length, head circumference using the 3D camera.
- 2-3 years of relevant experience in the industry.
- You have a keen sense of complexity estimation, a paranoia for writing efficient code.
- Very strong linear algebra fundamentals.
- Reasonable DSP skills.
- Experience with supervised as well as unsupervised learning algorithms.
- Most importantly, the ability to connect the usage scenarios of a system with its basic specifications.
- The flexibility to feel at home in a technology start-up with a small team demonstrates adaptability to fast-changing needs.
- Previous experience in a startup or a fast-growing company is a big plus.
- Good applied statistics skills such as distributions, statistical testing, regression, etc
- Proficient with Python, Keras, TensorFlow
- Experience on ARM platforms
- Activity in open-source projects and community leadership (presence at conferences, meetups).
- Experience in software engineering and data engineering is a plus
- Strong mathematical background
- Masters in Computer Science or related branches.
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479 Jessie St, San Francisco, CA 94103, USA
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