Snap Inc. is a camera company. We believe that reinventing the camera represents our greatest opportunity to improve the way people live and communicate. Our products empower people to express themselves, live in the moment, learn about the world, and have fun together.
Snapchat is the camera used by millions of people every day to Snap with family, watch Stories from friends, see events from around the world, and explore expertly curated content from top publishers. In short, we are a passionate team working hard to build the best platform in the world for communication and storytelling.
We’re looking for a Software Engineer, Machine Learning to join Snap Inc! Working from Kyiv office, you will collaborate with researchers, engineers, and designers and develop machine learning frameworks to create exciting products and breakthrough interactive experiences for millions of Snapchatters around the world.
What you’ll do:
— Develop and deploy production-quality machine learning frameworks for mobile devices
— Explore and implement challenging state-of-the-art algorithms to move the needle in the machine learning area
— Evaluate the technical tradeoffs of every decision
— Perform code reviews and ensure exceptional code quality
— Work closely with other Snap teams to explore and prototype new product features
— Iterate quickly without compromising quality
— 3+ years of software engineering experience
— Bachelor’s degree in a technical field such as computer science or equivalent experience
— Experience working with machine learning frameworks such as PyTorch, TensorFlow, Caffe2 or related frameworks
— Experience developing and optimizing real-time software for mobile applications
— M.S. degree in computer science or related field
— Strong understanding of machine learning approaches and algorithms
— Expertise in any of the following fields: segmentation, object detection, classification, deep learning model optimizations (e.g. pruning, quantization, distillation)
— Ability to proactively learn new concepts and apply them at work