 
						AI Researcher @ VPTeam
2 weeks ago
Requirements PhD or Master’s in Mathematics, Statistics, Computer Science, Physics or related discipline, ideally with proven research excellence. Ability to work independently on technically complex problems from idea to implementation. Strong expertise in Python and PyTorch. Solid understanding of time-series forecasting, neural architectures for prediction, and quantitative risk metrics. Proven track record of exceptional technical achievement (e.g. high‑impact research, grants, profitable ML deployments). Located in Poland (or willing to relocate) -preference for Warsaw to enable regular in‑person discussions. Nice to Have Publications in top ML/AI conferences (NeurIPS, ICML, ICLR). Experience with transformers, mixture‑of‑experts models, or reinforcement learning. Knowledge of graph neural networks or structured data methods. Contributions to open‑source ML libraries. Previous work in quantitative finance or high‑frequency trading. What else is important We look for a “real nerd” mindset -someone passionate about deep technical work, not just managing it. No strict bias for/against corporate or startup backgrounds -what matters is technical excellence. Candidates must be hands‑on contributors who can execute their ideas without heavy team dependency. Prefer Poland-based, but will consider exceptional remote candidates. Who takes a final decision The final hiring decision will be made jointly by company leadership and the lead researcher. Our benefits Competitive salary -market or above, negotiable based on impact. Performance bonus -tied to clear, agreed, measurable KPIs. Profit-sharing opportunity -after one year, access to a trading system investment program. Conference & learning budget. Hybrid setup in Warsaw or fully remote from Poland. Who we are? We are a small research-driven firm building state‑of‑the‑art AI systems for algorithmic trading.Our mission is to forecast complex, dynamic systems -starting with financial markets -with extreme precision. Through this forecasting-first approach, we are developing systems that, over time, will meet the standard of general intelligence.We believe true innovation happens in small, highly technical teams where every person’s work has a direct and visible impact. Our R&D environment is our laboratory and our proving ground: research flows directly into production, and improvements are quantifiable in real time. Philosophy We combine scientific rigor with entrepreneurial agility.Our work is guided by clear, measurable objectives -every experiment has a defined success metric, and excellent work is rewarded with meaningful bonuses.We value people who own their craft, from conception to delivery, and who prefer solving real-world, high‑impact problems over chasing academic novelty alone. Face‑to‑face brainstorming (when possible) accelerates discovery, yet we respect focused, independent work and trust our researchers to execute without micromanagement. ,[Design, run, and evaluate scientific experiments for forecasting and risk‑management., Take full ownership of model lifecycle: hypothesis → data prep → model design → testing → integration into production., Benchmark models with transparent, reproducible experiments and clear performance reports., Collaborate closely with the leadership team and other researchers to iterate quickly., Translate promising research into robust, maintainable production‑quality code., Document findings, mentor peers, and contribute to the company’s knowledge base.] Requirements: Python, PhD, PyTorch, Forecasting, AI, Open source
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