Senior Computer Vision Engineer

In this role at Dexterity, you will be working on writing Computer Vision code and building Machine Learning models for computer vision. The role will involve understanding our current systems and their limitations and bringing your expertise in Computer Vision and developing ML models. Additionally, you will be responsible for updating and scaling our current ML pipelines to cover more scenarios and improve accuracy. You will leverage your expertise around the subfields of semantic segmentation and instance segmentation, keep up to date with the latest developments in these areas and implement them using platforms like Pytorch, Tensorflow etc... Experience with RGBD datasets and point clouds is very important to the type of problems you will encounter in this role and experience in the areas of ML and CV for autonomous vehicles or robotics is very useful. In addition, a solid grounding in writing optimized code in C++ and Python. Additionally, familiarity with cloud infrastructure to build training and serving pipelines is also a key aspect to this role. At Dexterity, our use cases require low latency inference that approaches real time and therefore you must be able to build highly performant models and serving architectures. While an understanding of open source solutions is a useful prerequisite, we also require that the candidate has experience building their own models and setting up training pipelines. The end to end process of gathering, augmenting, labeling data and curating datasets, studying performance and optimizing quality of the model, as well as training, deploying and troubleshooting models on the field will be under your purview. About Dexterity At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work. We’re starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses around the world.   Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities.  Our systems are software-driven, hardware-agnostic, and have already picked over 15 million goods in production.  And did we mention we’re customer-obsessed?  Every decision, large and small, is driven by one question – how can we empower our customers with robots to do more than they thought was possible? Dexterity is one of the fastest growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures.  We’re a diverse and multidisciplinary team with a culture built on passion, trust, and dedication.  Come join Dexterity and help make intelligent robots a reality! Equal Opportunity Employer We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Required Skills: BS/MS in Computer Science, Machine Learning or a related discipline, or equivalent experience 5 or more years of related work experience Experience with OpenCV and Open3D Prior experience building, training and deploying production ML models from scratch using PyTorch and Tensorflow Strong knowledge of Modern C++ and Python Experience using profilers and debuggers to optimize code Experience building and maintaining production code Experience with serving architectures like NVIDIA Triton, TorchServe and Tensorflow Serving, Flask and others Strong academic background and knowledge of ML and academic papers Experience with cloud infrastructure such as AWS, GCP, Azure etc. and experience using this infrastructure to create training and serving pipelines Ability to trace and solve problems across interconnected systems, pipelines and applications Experience with Git and modern CI pipelines Nice to haves: Experience with Docker and Kubernetes Previous startup experience

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