Senior GenAI Data Scientist (m/f/d)

At AutoScout24, we’re excited to be hiring for our Canadian company, Trader Corporation - a key part of our international family.

As the Canadian arm of Europe’s largest online car marketplace, Trader Corporation plays a vital role in transforming how people buy, sell, and finance vehicles. With well-known brands like AutoTrader.ca, AutoSync, and Dealertrack Canada, Trader Corporation is driving digital innovation in the automotive industry — now reaching over 25 million Canadians every month.

What You’ll Do 

• Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.
• Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs.
• Define evaluation strategies, build ground-truth datasets, and create automated test and monitoring setups to ensure stable long-term model performance and proactively detect issues such as drift or hallucination.
• Collaborate with engineering, data, and product teams to integrate AI components into platforms, workflows, and customer-facing products, designing clean APIs, robust pipelines, and scalable deployment patterns.
• Act as a hands-on expert for GenAI topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, observability, and documentation across the organisation.
• Experiment with new tools, models, and architectures, identify high-impact AI opportunities, and build prototypes that can scale into production-ready solutions. 

What you’ll bring: 

• A degree in computer science, data science, engineering, or a related field.
• Experience building agentic GenAI systems in production (e.g., LangChain, AutoGen, Atomic Agents, or similar frameworks).
• Strong coding skills in Python and experience with robust software engineering practices.
• Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows.
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