Architect of Autonomous Research Platform
1w ago
WorldwideSeniorHybridB2ragfine-tuningprompt engineeringpythonpytorchjaxstatistical designagent systems
The role involves building from scratch an agent-based research and execution platform for a pioneering AI research company focused on autonomous systems, starting within financial markets and expanding to life sciences, biotech, and physics.
About the company
- Our client is an AI research company building a system that can formulate hypotheses, design experiments, train models, and discover answers — without human intervention.
- Their first domain is financial markets: fast feedback loops, high-quality real-world data, rapid iteration.
- They are not a traditional trading firm. They see themselves as a research lab building frontier AI systems.
About the product
- A fully automated pipeline covering hypothesis → research → validation → execution → optimization handled by agent-based systems.
Responsibilities
- Design and implement a multi-agent orchestration framework (roles, communication, memory, decision loops).
- Build retrieval and knowledge systems grounded in market data and research.
- Develop a Strategy DSL and compiler for research → simulation → production.
- Create falsification-first evaluation systems to eliminate false alpha.
- Design an “alpha memory” layer to accumulate knowledge and avoid repeated mistakes.
- Work closely with researchers and engineers to bring ideas into low-latency production.
- Define robustness metrics beyond P&L (stability, execution realism, capacity, novelty).
Requirements
- LLM architecture expertise: RAG, fine-tuning, prompt engineering, and evaluation frameworks.
- Agent systems experience: Building multi-agent orchestration, memory management, tool use, and collaboration (beyond basic LLM integrations).
- Experience creating auto-researcher / co-scientist systems: Proven track record of building autonomous research agents or AI systems that assist scientists/analysts.
- Strong Python + ML skills: Production-ready code with PyTorch, JAX, or similar frameworks.
- Statistical rigor: Experimental design and statistics for non-stationary, noisy environments.
- Systems thinking: Ability to design abstractions, interfaces, and pipelines - not just models.
- English proficiency: B2+
Nice to have
- HFT/MFT experience or low-latency mindset (nanosecond-scale, hardware-aware, deterministic design).
Conditions
- Compensation: up to €15,000 gross/month, based on experience (open to discussion).
- Locations: Netherlands (Amsterdam), UAE (Dubai) - relocation support provided; or UK (London) / Canada (Montreal) if you're already based there - official employment arranged.
- Access to alternative high-performance computing architecture (beyond GPUs).
- Research-driven environment with real-world impact and encouragement to publish.
- Small, fast-moving team — your contribution has direct impact.
How to apply
- In your message, please include 3–5 lines about your experience with LLMs and AI agents, and whether you have built auto-researcher or co-scientist systems — this helps us quickly assess the fit.
Found in@datasciencejobs