Job description
About the role:
We're looking for a Staff Data Scientistto lead the technical direction, scaling, and evolution of our core AI capabilities across two tightly connected domains:
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Search, Ranking & Recommendations: advancing our multi-stage retrieval and ranking systems (Two-Tower networks, Vector Search/ANN, LTR) to optimize catalog discovery for raw physical products and designs, with a particular focus on multimodal and sequence embeddings.
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Generative AI & Visual ML: scaling our image intelligence pipeline by combining multimodal generative models with classical and deep computer vision. You'll drive systems that generate rich features and embeddings for recommendation engines, as well as tools that help merchants with content creation, smart product delayering, and automated visual asset processing.
You'll lead the modeling strategy and collaborate across our data science and machine learning engineering teams, advancing our production systems from early successes to enterprise-grade AI infrastructure.
Your daily tasks will include:
Leading & scaling recommendation and search systems
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Lead the architectural direction for candidate retrieval, multi-objective ranking, and learning-to-rank (LTR) models across raw product and design recommendations.
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Advance our personalization engines, incorporating sequence embeddings of merchant history, niche trends, and sales performance signals to surface the best products and designs.
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Connect downstream merchant sales and conversion data back into upstream design generation and candidate ranking models to continuously improve recommendation relevancy.
Driving AI design generation & vision pipelines
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Oversee image generation pipelines that combine LLMs/multimodal models with deep learning architectures (e.g., diffusion models, UNets, Vision Transformers) to generate high-converting designs for merchants.
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Deepen our classical computer vision capabilities (OpenCV) alongside deep learning vision models (e.g., ResNet, CNNs, YOLO/segmentation networks) for delayering, automated background separation, print-area quality analysis, and asset validation.
Driving end-to-end product innovation (maker focus)
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Act as a product engineer with full technical autonomy across the stack — from foundational model selection (fine-tuning, prompt engineering, self-hosting) to serving pipelines and frontend workflows.
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Rapidly prototype, iterate, and ship complete agentic pipelines and ML features using AI-assisted development (Gemini for ideation and research; Claude Code and Claude Cowork for rapid implementation).
Technical leadership, governance & mentorship
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Define and refine online/offline evaluation frameworks (NDCG, MRR, visual quality metrics, merchant conversion uplift) and oversee our continuous A/B testing strategy.
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Guide strategic make-vs-buy decisions, API vs. self-hosted fine-tuning trade-offs (e.g., open vision models, LLMs/multimodal models), and inference optimization.
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Set standards for applied ML across the organization, mentor senior ICs, run design reviews, and foster a culture of shipping measurable business impact.
Your qualifications:
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Experience: 8+ years of hands-on experience building, deploying, and scaling production ML systems, with a proven track record of staff-level technical leadership.
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Search & RecSys expertise: deep expertise in modern search, candidate generation, and recommendation architectures (Two-Tower models, ANN vector indexing, Transformer rerankers, learning-to-rank algorithms).
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Computer vision & generative AI expertise: hands-on experience with classical CV (OpenCV) and modern deep vision architectures (CNNs, Vision Transformers, diffusion models, multimodal LLMs/CLIP) for image processing and generative workflows.
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Closed-loop ML: a proven ability to build systems that feed downstream business outcomes (clicks, conversions, sales) back into upstream model training and generation logic.
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Technical stack: fluency in Python and the modern AI/ML stack, anchored in PyTorch for deep learning and vision models, alongside LLM orchestration and agentic frameworks (e.g., LangChain, LangGraph). Practical experience with production serving patterns (FastAPI, event-driven async processing), MLOps tools (CometML, Flyte), and cloud data warehouses (Snowflake).
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AI-assisted workflow: comfort leveraging AI tools across the workflow — Gemini for ideation and research, alongside Claude Code and Claude Cowork for rapid prototyping, system design, and production code development.
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Product maker mindset: a proven track record of taking full technical ownership of end-to-end features. You treat ML systems as products and are comfortable making architectural decisions across the whole stack, from model selection down to frontend API integration.
Nice to have: experience in e-commerce, two-sided marketplaces, or creator platforms.
Our Stack & Tooling:
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Deep Learning & Computer Vision: PyTorch, OpenCV, Hugging Face Transformers, Diffusers
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LLMs & Agentic Systems: LangChain, LangGraph; hosted APIs (Gemini, OpenAI) and open multimodal models (FLUX, Qwen); Claude Code and Claude Cowork for software engineering
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Search & Retrieval: Vector databases (Qdrant / Pinecone / FAISS), Two-Tower ranking, Snowflake
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Workflows, MLOps & Experimentation: Flyte for workflow orchestration; CometML for experiment tracking, model registry, and CI/CD artifact management; Amplitude for A/B testing and feature flags
What we offer:
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A global, inclusive team that’s as supportive as it is ambitious and serious about getting things done
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An opportunity to work remotely or in a modern and welcoming office in Riga
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Flexible working hours (start your day as late as 11 AM)
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Private health insurance
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2 extra paid days off to focus on your mental or physical well-being
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1 extra paid day off to celebrate a Birthday or any other celebration of your choice
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Internal and external learning opportunities
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Access
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