Architect of Autonomous Research Platform

Навыки

• Дообучение моделей
• LLM
• Machine Learning
• P&L и бюджет
• Prompt engineering
• Python
• PyTorch

Задачи

• 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)
• We're looking for an AI Architect to build from scratch an agent-based research and execution platform — the foundation of a fully autonomous AI Scientist
• The Project
• 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
• But the long-term vision goes far beyond trading — into life sciences, biotech, and fundamental physics
• They are not a traditional trading firm. They see themselves as a research lab building frontier AI systems
• The long-term vision
• a fully automated pipeline where the entire lifecycle
• hypothesis → research → validation → execution → optimization
• is handled by agent-based systems

Требования

• 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+
• 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

Будет плюсом

• HFT/MFT experience or low-latency mindset (nanosecond-scale, hardware-aware, deterministic design)
• What’s Offered
• 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
• Contacts
• If you're excited about building autonomous systems that go all the way from research to execution - DM @sobolevavalery

Паспорт вакансии

История публикации

Откуда что взялось

Отмечено то, что вывели мы. Без пометки — значение назвал работодатель.

Почему на этом месте в выдаче

Порядок выдачи объявлен контрактом: свежесть решает между днями, полнота и зарплата — внутри дня.