Requirements:

• 8+ years of experience in applied AI, ML, or software engineering
• Proven track record of shipping ML or AI systems to production at scale
• Deep experience with search, retrieval, ranking, recommendation systems, or assistants
• Strong understanding of modern deep learning, especially transformers and embeddings
• Experience with LLM integrated or knowledge intensive systems
• Experience designing evaluation frameworks and metrics for ML systems
• Strong programming skills in Python and at least one of Go, C++, or similar
• Ability to operate in a fast moving, product-driven environment with high ownership and autonomy

Nice to Haves:

• Experience with large-scale search or recommendation systems
• Background in agentic AI systems (agents, tool use, autonomous workflows)
• Experience with RAG, multi-step retrieval, or tool use
• Publications, open source, or similar signals of technical depth and impact

What You'll Be Doing:

• Designing agent native retrieval systems optimised for machine consumption rather than human search UX
• Building systems where LLMs iteratively plan, query, refine, and reason over results
• Developing ranking and retrieval approaches for multi-step, agent-driven workflows under real-world constraints

Perks and Benefits:

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams