Who are we?Our mission at Webiks is to create powerful
Webiks
Israel
לפני 4 שנים Full-time
Who are we?Our mission at Webiks is to create powerful data-driven applications and models that help our clients innovate and grow. We build custom software and custom models for clients from multiple industries including Defense Security Health and Automotive. We think long-term. Forming long-lasting strong relationships and partnerships with our clients is at the core of our strategy. Who you are?As a Computer Vision Engineer you will have an important role in our Data Science and AI team. You are a Deep Learning enthusiast with a significant hands-on experience with deep convolutional neural networks for detection classification and segmentation of images and objects. You understand that sometimes good old ML modeling and classical image and signal processing techniques are essential and you enjoy combining them with end-to-end DL approaches. What’s this job about?As a Computer Vision Engineer you will be responsible for:Design develop and train state-of-the-art computer vision algorithms. All the way from rapid prototyping to production-ready models (object detection fine-grained object classification change detection and more).Collaborate with engineers in our data-science full-stack software development and product-management teams - to implement value-adding solutions.Evaluate your results and improve your solutions based on business metrics and scientific train-val-test methodologies. Explore innovative techniques such as active-learning self-supervised learning and generative models and evaluate their usability to our use-cases. Drive the end-to-end execution of Computer Vision projects including understanding the requirements and goals set the criteria data exploration model selection training and evaluation all the way to full-scale implementation and integration. Provide continuous feedback and support to fellow Data Scientists in the team all of them are brilliant minds and enthusiastic people just as you are some of them are less experienced than you.Maintain a highly cross-disciplinary perspective solving issues by applying approaches and methods from across a variety of Data Science disciplines and related fields. Your day-to-day will be focused on Computer Vision but you will also be involved in exploratory projects in the fields of structured data and time-series ML NLP and competitive Data Science. Continuously evolve yourself by keeping up to date with the latest Data Science Machine Learning & Deep Learning technologies.You’ll be reporting to our CTO. RequirementsPersonalYou flourish when you are surrounded by talented sharp-minded people.You love doing things yourself. You like mentoring others.You are a great communicator. You write you talk you appear you communicate. You are open. You understand that the only reason you have reached so far is that you were able to stand on the shoulders of giants. You truly believe the principles of the open movement - Open Source Open Data & Open Innovation. You are a competitor. “Bestfitting” Kaggle winner is your role model. TechnicalDeep technical expertise in Computer Vision and Deep Learning. BS/MS degree in Computer Science Engineering or a related field. At least 3 years of successful hands-on ML/DL/DS positions with a significant Computer Vision experience.You can code. Your code quality meets the typical Software Engineering standard (and not only the typical Data Science standard). Proficient in Python.Experience with machine learning frameworks and libraries Pytorch Keras).Experience with overhead imagery (aerial / satellite imagery) and with GIS - an advantage.Experience with Active Learning techniques - an advantage.Experience with cloud computing environments (e.g. AWS Azure) and relevant execution frameworks Kubernetes - an advantage.You are comfortable at reading academic papers and reproducing their
python
software
integration
software development
computer science
machine learning
algorithms
software engineering
training
engineering
cloud computing
management
security
strategy
aws