Senior AI Engineer

01. ABOUT THE COMPANY

Dizzaract is a product-driven company operating at the intersection of gaming, digital platforms, and AI. We build and scale multiple products — including Farcana, Gamed, and FAR Labs — each exploring a different space, but united by a shared approach: moving fast, staying curious, and focusing on things that people actually use. We operate as a collaborative, non-hierarchical team where ideas are valued based on their impact, not theirorigin, and where AI is embedded across everything we build — from infrastructure to product decisions.

02. ABOUT THE ROLE

We’re looking for a Senior AI Engineer to design and ship production AI systems powering GAMED.

This role focuses on applied AI — not research for the sake of research. You’ll work on recommendation systems, AI-driven moderation, retrieval systems, agentic workflows, ranking systems, and player-facing AI features integrated directly into the product ecosystem.
You’ll collaborate closely with Backend, Product, and Infrastructure teams to build scalable AI systems used by real users.

03. WHO YOU ARE

• You think pragmatically about AI products and infrastructure.
• You care about reliability, evaluation, and production quality.
• You’re comfortable building systems from experimentation to deployment.
• You understand both model quality and infrastructure cost.
• You enjoy solving applied ML problems in live environments.

04. RESPONSIBILITIES

• Design and deploy AI-powered product features.
• Build recommendation, ranking, moderation, and agent systems.
• Develop and optimize RAG pipelines.
• Work with modern LLM ecosystems and open-weight models.
• Design evaluation frameworks and testing pipelines.
• Optimize inference, retrieval, and deployment performance.
• Collaborate closely with backend and infrastructure teams.

05. REQUIREMENTS

• 5+ years in engineering.
• 3+ years building applied ML/AI systems in production.
• Strong Python expertise.
• Experience with PyTorch or JAX.
• Experience with LLMs, RAG, and agent systems.
• Experience with vector databases and retrieval systems.
• Understanding of model evaluation and deployment strategies.
• Experience balancing quality, latency, and infrastructure cost.

06. NICE TO HAVE

• RLHF / DPO / PPO experience.
• Multi-agent systems.
• Recommender systems at scale.
• MLOps tooling.
• AI safety / red-teaming experience.

07. WHAT WE OFFER

• Real ownership and direct impact on a global AI infrastructure product.
• Fast execution, low bureaucracy, and a highly collaborative, idea-driven team.
• Exposure to cutting-edge AI, gaming platforms, and digital asset economies.
• Competitive salary with performance-based incentives.
• 24 days annual leave, plus public holidays.
• Health insurance.
• Modern office in Yas Creative Hub.
• Continuous learning through real-world problem solving — not just theory.
• The opportunity to shape what you're working on and influence product direction.
• A diverse, open-minded team where ideas are genuinely heard.

Work Location: In person