We are one team collectively focused on creating an unrivaled experience for our customers and Contributors. Our principles represent the mindset of the employee who will thrive at SensAI. If you are passionate about what you do, and want to become part of a cutting-edge technology company building industry leading products, please apply. Opportunities: Personal, technical, and professional growth. Opportunity to work in a fast-paced fast-growing team.
– 1+ years of experience with common toolkits, such as TensorFlow, Caffe, Torch/PyTorch
– 1+ years of industry experience creating, deploying, and learning from production algorithm analysis
– Fluent in one or more general purpose programming languages including but not limited to Python, Matlab, Spark, C++
– Excellent applied statistics skills, such as distributions, statistical testing, regression, etc.
B- S or MS in Computer Science or equivalent experience
We are one team collectively focused on creating an unrivaled experience for our customers and Contributors. Our principles represent the mindset of the employee who will thrive at SensAI. If you are passionate about what you do, and want to become part of a cutting-edge technology company building industry leading products, please apply.
Your primary focus will be in applying computer vision techniques, AI algorithms in the areas of deep learning and machine learning, doing statistical analysis and building high quality end-to-end systems integrated with client products and solutions. This is a long term paid opportunity and along the way you will be collaborating with an extremely talented and passionate team of researchers, data scientists and engineers working for SensAI.
We are a fast growing computer vision startup with unique products and recently going through a series of funding applications.
– Software development with innovative deep learning and machine learning algorithms
– Exploring immense data sets of information from images, videos, customer interactions, and marketing
– Selecting features, building and optimizing classifiers using machine learning techniques
– Enhancing data collection procedures to include information that is relevant for building analytic systems
– Processing, cleansing, and verifying the integrity of data used for analysis
– Creating automated anomaly detection systems and constant performance tracking
– Working with product manager, data engineers and business partners to drive ideas from the rapid prototyping phase all the way through to serving and learning from live traffic at scale
For your questions, send an e-mail to firstname.lastname@example.org