As a member of our Synthetic Data Generation Team, you will be responsible for improving data generation pipelines by experimenting with synthetic data and providing feedback to the development team. You will closely collaborate with members of our Research teams to drive your research in a way that will improve reliability of existing models and reduce time-to-market of new features that are only planned to be developed.
—Ability to provide constructive feedback
—2+ years in machine learning (computer vision domain)
—Practical experience in at least one of the following problems: classification, detection, segmentation.
—Knowledge of following Deep Learning frameworks: PyTorch is a must; TensorFlow or Keras is a plus.
—Good understanding of Machine Learning and Deep Learning concepts
—Understanding of Python’s built-in algorithms and data structures, their time and space complexities
—Good written and spoken English
— Practical experience with GANs, VAEs
— Probabilistic programming and bayesian framework
— Model optimization: pruning, quantization, knowledge distillation
— Basic understanding of web and client-server architecture
— asyncio, aiohttp, and other async libraries for back-end
— Basic understanding of Big Data, understanding of difference between MapReduce and in-memory processing
— Algorithms, data structures
— SQL, NoSQL
— Docker, Kubernetes, Kubeflow
— Working on impactful security products and the opportunity to use them personally
— Competitive salary and perks
— PE accounting and support
— WFH and remote working mode possibility. Partial furniture compensation
— Social package, including medical insurance available from the start date and sports compensation after the trial period
— 21 paid vacation days per year, paid public holidays according to the Ukrainian legislation
— Educational possibilities like corporate courses, knowledge hubs, and free — English classes. Semiannual performance review
— Free meals, fruits, and snacks when working in the office.