About the job
SKELAR is a venture builder that creates international tech companies adhering to the principles of the venture investment landscape. We collaborate with co-founders to assemble strong teams and launch product-oriented IT businesses that can compete on global markets.
We are currently expanding our team and seeking a Lead AI/ML Engineer to spearhead the development of our flagship product - a personalized AI Stylist.
Dressly, which began operations in 2024, has quadrupled its growth in just the past six months. By 2026, we aim to achieve quintuple growth compared to 2025. Our user base is steadily increasing, and they are already fans of our AI features: Virtual Try-On, Color, Body, and Outfit Analysis. Therefore, we are building internal expertise at Dressly and are in search of a Lead AI/ML Engineer to lead the development of our key product - a personalized AI Stylist.
Why join us now? This is your chance to become an architect of AI strategy at an early stage, build your own team from the ground up, and create a product that will transform the fashion experience for millions of users.
Technology Stack: We are looking for a leader who will take responsibility for the final selection of tools and architectural patterns. Currently, we are focusing on the following stack, but you will need to choose and implement many components or their equivalents independently:
- Languages and Frameworks: Python (PyTorch / TensorFlow / JAX)
- GenAI & LLM: LangChain / LlamaIndex, Vector Databases (Pinecone, Milvus or equivalents)
- Infrastructure & MLOps: GCP (Vertex AI, GKE), Docker, Kubernetes, MLFlow or other tools for orchestration and monitoring of models
- Data: PostgreSQL, BigQuery, ETL process tools
What matters to us:
- You have 5+ years of experience in ML/AI and a successful background in building systems from scratch (from R&D to Production).
- A deep understanding of the GenAI ecosystem: knowledge of LLM architectures, fine-tuning methods, and RAG (Retrieval-Augmented Generation).
- Expertise in Computer Vision and RecSys: experience with generative image models (VTON) and building personalized recommendation systems.
- An engineering mindset: you understand the mathematics 'under the hood' and can build stable data pipelines and ML services.
- Pragmatism and business focus: you can align technical solutions with business goals.
