AI Research Engineer
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Job overview
Smart Bricks is seeking an AI Research Engineer to improve the performance of its intelligence systems. The role bridges research and production, focusing on real estate reasoning, financial analysis, document understanding, and long-horizon agentic tasks. The engineer will explore models and agent architectures, develop domain-specific datasets and evaluation methods, and translate successful research into production systems. Publications are welcome but not required.
Skills & qualifications
Skills
Full job description
Smart Bricks is the applied AI lab for real estate. We are building the intelligence infrastructure for the world’s largest asset class. Our platform combines four intelligences: Company Brain, Real Estate Intelligence, Market Intelligence and Specialist Agents, with Financial Engines under the agents. We operate globally across Dubai, London and San Francisco, bringing together exceptional people from AI, engineering, real estate and finance. We care more about exceptional ability, rate of learning and ownership than conventional credentials.
The role Your job is to push the performance frontier of Smart Bricks’ intelligence systems. You’ll work between research and production, exploring how models can become materially better at real estate reasoning, financial analysis, document understanding and long-horizon agentic tasks.
What you’ll do
- Develop evaluation suites for real estate and financial reasoning
- Experiment with frontier and open-source models
- Fine-tune and adapt models for domain-specific tasks
- Research reasoning, planning, memory and agent architectures
- Build synthetic and expert-labelled datasets
- Develop techniques for increasing reliability and reducing hallucination
- Benchmark models across cost, latency and performance
- Turn successful research into production systems
What we’re looking for
- Strong ML and deep learning foundations
- Experience with LLMs, post-training, evaluations or applied NLP
- Strong Python and modern ML frameworks
- Experimental rigour and quantitative thinking
- Ability to translate research into production impact
Publications are welcome. They are not required.
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