Teams at CommIT

Develop and deploy scalable, production-grade machine learning and AI solutions, including LLM-based systems and modern NLP applications. Collaborate with senior engineers to build reliable AI-driven financial research products. Responsibilities require strong Python and software engineering skills, deep learning framework experience, database knowledge, Docker, and familiarity with LLM/NLP technologies. Preferred experience includes RAG pipelines, vector databases, LLM fine-tuning, cloud platforms, and Kaggle competitions.

Develop computer vision and deep learning algorithms for detection, segmentation, tracking, and re-identification using large-scale video data. Prototype and evaluate models, analyze failures, optimize inference pipelines, and build production-quality Python solutions. Collaborate with R&D, backend, infrastructure, and QA teams to integrate algorithms into production systems. Support data collection and annotation, apply AI-assisted development tools, and improve model performance, scalability, and robustness.

Designs end-to-end distributed software solutions across AWS, Google Cloud, Azure, on-premises, and hybrid environments. Leads customer discovery, architecture discussions, solution presentations, and technical decisions; creates architecture documentation and proposals; guides development teams through implementation; and supports presales activities. Collaborates with infrastructure, cloud, data, and delivery architects on scalable, secure, observable systems, while promoting reusable architecture patterns and best practices.