Staff Data Scientist

Role overview Set technical direction for production machine learning across product discovery and visual AI. The work combines search, ranking, and recommendations with generative and computer vision systems, spanning model strategy, deployment, experimentation, and product workflows. You will guide senior contributors and help scale early capabilities into reliable infrastructure with measurable business impact.

Responsibilities - Shape candidate retrieval, ranking, and learning-to-rank systems for product and design recommendations. - Improve personalization using merchant history, trends, and sales signals, and feed conversion outcomes back into model training. - Guide image generation and vision pipelines for design creation, image separation, quality analysis, and asset validation. - Prototype and ship ML features across model selection, serving, and product integrations, including agentic workflows. - Establish offline and online evaluation, A/B testing, and inference optimization practices. - Make build-versus-buy and hosted-versus-self-managed model decisions; mentor senior individual contributors and set applied ML standards.

Requirements - 8+ years building, deploying, and scaling production ML systems, with staff-level technical leadership experience. - Deep knowledge of search and recommendation architectures, including two-tower models, approximate nearest neighbor retrieval, reranking, and learning to rank. - Practical expertise in computer vision and generative AI, including OpenCV and deep vision or multimodal models. - Experience building feedback loops that use clicks, conversions, or sales to improve models and generation. - Strong Python and PyTorch skills, plus experience with model serving, asynchronous processing, MLOps, and data warehouses. - Ability to make technical decisions across the stack and communicate direction through design reviews and mentorship.

Nice to have - Experience in e-commerce, marketplaces, or creator platforms. - Familiarity with vector databases, workflow orchestration, experiment tracking, and A/B testing tools.

Benefits and work setup - Remote work or an office option in Riga, with flexible start times as late as 11 a.m. - Private health insurance, additional paid wellbeing and celebration days, learning opportunities, mentorship, meetups, and hackathons. - Office lunch in Riga and an employee merchandise discount.