Responsibilities

• Research and Development: Stay at the forefront of generative AI, deep learning, and associated areas through diligent research. Test various generative models, architectures, and algorithms to advance our technological capabilities
• Model Development: Architect, build, and roll out innovative generative models specific to desired applications. Engineer and refine deep neural networks, variational autoencoders (VAEs), generative adversarial networks (GANs), among other structures, to produce authentic and assorted synthetic data
• Data Preprocessing: Collaboratively work with data engineers and domain specialists to prepare and refine large-scale datasets. Implement statistical methods and data augmentation techniques to guarantee superior quality training data for generative models
• Model Training and Evaluation: Educate and fine-tune generative models using extensive datasets, utilizing approaches like transfer learning and unsupervised learning. Create metrics and benchmarks to judge model effectivity and produce insights that urge model enhancements
• Collaboration: Work alongside a varied team of data scientists, software engineers, insurance experts, and experience designers in integrating generative models into practical applications. Offer technical leadership and support to ensure efficient execution and deployment of generative AI solutions
• Innovation and Optimization: Investigate novel methods, frameworks, and tools to improve and optimize generative model performance. Stay informed of new trends and standard methodologies in the field and contribute to enhancing the organization's data science capacities
• Documentation and Reporting: Compile precise and clear technical documentation covering model structures, methodologies, and experimental results. Share insights and findings with both technical and non-technical audiences enhancing knowledge exchange and decision-making processes

Requirements

• Extensive experience with the development and application of generative models, including GANs, VAEs, and deep generative models
• Proficiency in programming languages like Python and in utilizing deep learning frameworks such as TensorFlow or PyTorch
• Solid grasp of concepts in machine learning, deep learning, and statistical modeling
• Background in handling large-scale datasets and applying preprocessing techniques
• Skill in data visualization and exploratory analysis tools
• Excellent problem-solving capabilities with a creative approach to devising innovative solutions
• Strong written and verbal communication abilities suited for explaining complex technical topics to diverse audiences
• Established track record of teamwork and engagement in multifaceted projects
• Robust research and self-learning skills, with an enthusiasm for keeping abreast of latest developments in generative AI and related fields

Nice to have

• Background in natural language processing (NLP) and text generation models
• Familiarity with cloud-based machine learning solutions and Generative AI services, such as Azure (Open AI, ChatGPT), Google Cloud, or AWS
• Knowledge of parallel computing and distributed training frameworks
• Contributions to the research community in generative AI or affiliated areas

We offer

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Consider relocation options in over 30 countries worldwide
• Participate in volunteer, charity programs and communities (both technical and interest-based)
• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)
• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program - a free programming language training program for EPAMers' children