AI Product Engineer — Early-Stage AI SaaS Startup İş İlanı

ABOUT THE COMPANY VendiLabs is an early-stage startup building AI-first SaaS products . We are building a small, ambitious, and highly hands-on core team. We value speed, strong engineering judgment, product-oriented thinking, ownership, curiosity, and the ability to learn and execute quickly. Our goal is not to build AI demos or simple wrappers around existing models. We want to build AI-powered products that solve real user problems, deliver measurable value, and can scale globally . Joining at this stage means having the opportunity to directly shape our products, AI systems, technical foundation, and product direction from the ground up. ABOUT THE ROLE We are looking for a hands-on AI Product Engineer who can work across AI/ML engineering, LLM systems, software development, and product . You will take ownership of AI capabilities end-to-end, from understanding the product problem and choosing the right technical approach, including training, fine-tuning, or adapting models when needed , to implementation, evaluation, optimization, deployment, and continuous improvement in production. We care less about using the most advanced technique and more about choosing the right approach for the product . RESPONSIBILITIES • Designing and building AI-powered product features from

idea to production • Integrating and orchestrating LLMs, multimodal models, and open-source models • Designing and building RAG, embeddings, retrieval, tool calling, agent workflows, and memory/context systems • Preparing datasets and training, fine-tuning, or adapting ML / deep learning / LLM models when required • Building recommendation, classification, prediction, personalization, or other ML systems when appropriate • Evaluating models and AI approaches based on quality, accuracy, latency, reliability, and cost • Developing backend services, APIs, data pipelines, and infrastructure required for AI-powered features • Designing evaluation processes, identifying hallucinations and failure cases, and improving systems using production data and user feedback • Optimizing inference, model routing, caching, context usage, and token consumption for performance and cost • Working closely with the Founder, Technical Lead, and engineering team on product and technical decisions • Helping determine where AI creates real product value - and choosing the right technical approach accordingly WHAT WE ARE LOOKING FOR • Strong hands-on Python experience and solid understanding of machine learning / deep learning fundamentals • Hands-on experience training or fine-tuning ML / deep learning models , including dataset preparation, training, validation, and evaluation • Experience building AI or LLM-powered applications beyond simple API integrations • Understanding of modern LLM systems such as RAG, embeddings, tool calling, agents, and context management • Experience working with APIs, backend systems, databases, and data pipelines • Ability to evaluate AI systems across quality, latency, reliability, scalability, and cost • Strong product thinking and ability to connect technical decisions with real user value • Ability to learn quickly, investigate unfamiliar problems independently, and take broad ownership in an early-stage environment • Professional working proficiency in English and ability to work closely with the core team in Istanbul • Degree in Computer Engineering, Software Engineering, Computer Science, Electrical & Electronics Engineering , AI/Data-related fields, or equivalent practical experience PREFERRED TECHNICAL BACKGROUND You are not expected to know every technology below, but experience with several will be a strong advantage: • Programming: Python, TypeScript / JavaScript • ML / Deep Learning: PyTorch, TensorFlow, scikit-learn • Model Ecosystem: Hugging Face Transformers, PEFT, TRL • LLMs: OpenAI, Anthropic Claude, Gemini, open-source models • Fine-Tuning: LoRA, QLoRA, SFT, PEFT • AI Systems: RAG, embeddings, vector search, reranking, agents, tool calling, memory/context systems • AI Frameworks: LangChain, LangGraph, LlamaIndex or similar • Vector / Data: pgvector, PostgreSQL, Supabase, Redis, vector databases • Backend: FastAPI, Node.js, REST APIs • Infrastructure: Docker, CI/CD, AWS or GCP • AI Quality: evaluation frameworks, observability, failure analysis, monitoring • AI Optimization: model routing, caching, token optimization, inference optimization, latency and cost management STRONG ADVANTAGES • Building and shipping your own AI products, SaaS products, web/mobile applications, or side projects • Taking an AI product or feature from 0 → 1 → production • Having a GitHub profile, portfolio, research project, or live product demonstrating what you can build • Experience training or adapting models for a specific domain or user problem • Experience building production RAG, agentic, recommendation, personalization, or prediction systems • Experience improving AI systems using real user feedback and production data • Experience deploying and operating AI systems used by real users • Experience in an early-stage startup or small, fast-moving product team • Experience working across both AI engineering and product development We care about what you can build, how you think, your technical depth, your product judgment, how quickly you learn, and the ownership you take . We are currently building our core team and reviewing applications.