A Look Inside the Role：If you are a strong applied scientist with a background in computer vision, and are passionate in applying your skills to solve customer problems in a fast-growing startup, then this is the right opportunity for you. IoT is a perfect area for landing AI technologies, and Wyze provides the unique opportunity for landing AI technologies into products with millions of users which are still growing at a fast pace. As a Senior Research Scientist, you will help solve a variety of technical challenges. Since this is an early-stage effort in a startup environment, you will play an active role in translating business requirements into elegant and beautiful solutions and build quick prototypes or proof-of-concepts in partnership with other passionate people in an international team. When you join the team, we guarantee that you will learn a ton, have fun and make a positive impact on millions of users. You will work with a team of highly skilled and motivated scientists and engineers, with the mission to build smart living for everyone, using machine learning and deep learning and solving problems in computer vision, sound detection, and speech recognition. As part of your job, you will collect the requirements, define the problems, define the algorithms, conduct proof-of-concepts with stringent performance requirements (e.g., accuracy, speed, model size), perform offline and online testing, and push models to production. Responsibilities职责：1. Help invent, build and monitor the performance of state-of-the-art machine learning models for a variety of tasks such as object detection, face recognition,pose estimation, event recognition, object tracking, sound detection, speech recognition.2. Collaborate with data engineers and software developers on building data pipelines to ingest, process and analyze data that are important to computer vision models.3. Collaborate with other scientists and engineers on building the AI platform for model training, evaluation and deployment.。4. Collaborate with software developers on how to productionize the models.5. Be proactive in understanding and questioning the quality of the provided data. Provide ways to monitor the quality of the data that is needed for building computer vision models and mitigate noise when necessary.6. Be proactive in diving deep on the strengths and weaknesses of the models, continuously evaluating them and suggesting ways to quantify the patterns of errors that the models make.7. Patent and publish findings in leading computer vision and machine learning conferences and journals.You Already Have These Qualifications and Love What You Do：1. PhD in CS or related fields.2. 2+ years of working experience or equivalent in using deep learning and machine learning to solve production problems.3. Deep understanding of state-of-the-art Deep Learning algorithms for Object Detection/Face Detection/Face Recognition and ability to implement them in product-quality code using both existing toolkits and self-developed code.4. Proficiency with at least one of the popular deep learning toolkits (PyTorch, TensorFlow, MXNet, DarkNet, Caffe, etc.)5. Proficiency with Python or C/C++ and at writing production-read codes.6. Excellent written and verbal communication skills, ability to communicate effectively to both technical and non-technical audiences.7. Strong publication records in top CV/ML conferences or journals, such as CVPR, ICCV, ICLR, ICML, ECCV, NeurIPS.And Even Better if the Following Applies to You：1. Experience in working with large-scale distributed machine learning algorithms, frameworks, and systems.2. Ability to prioritize and strategize in a variety of project areas and deal with ambiguity in a fast-paced, entrepreneurial environment.3. Solid experience in AWS, Azure or Google Cloud.