Deep Learning Researcher
SeniorLead ML/DL research for time-series forecasting and next-generation trading systems.
About the role
We’re looking for a Senior Deep Learning Researcher to lead ML/DL research for time-series analysis and forecasting of financial-market behavior. The role blends research, production ML/DL development, and technical leadership: you set the research direction, help shape model architecture, lead research initiatives, and work with the Quant Research team on next-generation trading systems.
What you’ll do
- Set the ML/DL research direction for financial time-series analysis
- Design and build production ML/DL models
- Research and ship modern Deep Learning architectures for forecasting and sequential modeling
- Lead research initiatives and mentor the ML/Research team
- Work with the Quant Research team on strategies and capital-management systems
- Form hypotheses, design experiments, and analyze results
- Analyze large volumes of historical and streaming data
- Track research in Machine Learning, Deep Learning, Reinforcement Learning, and Quantitative Finance
- Help shape the product’s long-term ML strategy
Requirements
- Degree from a strong technical university (MIPT, HSE FCS, MSU, ITMO, SPbU, Bauman MSTU, Innopolis, or similar)
- 3–4+ years of commercial experience in Machine Learning / Deep Learning or algorithmic trading
- A proven track record building and shipping production ML/DL models for time series
- A strong track record at Big Tech, a Prop Trading firm, Hedge Fund, or FinTech
- At least one year leading a research-heavy team
- Deep understanding of modern Machine Learning and Deep Learning methods
- Hands-on with time series, feature engineering, and model evaluation
- Strong Python
- Hands-on with PyTorch, Scikit-Learn, CatBoost, LightGBM/XGBoost, and Optuna
- Experience building full-cycle ML systems — from research to production
- Our team works in Russian; English at a level to read research papers and documentation
Nice to have
- Hands-on algorithmic-trading experience
- Experience with reinforcement learning
- Experience with market data (order book, trades) or high-frequency time series
- Understanding of quantitative finance and risk management
- Publications, Kaggle, ICML/NeurIPS/ICLR, or other research projects
- Open Source projects in Machine Learning
What we offer
- Office in the center of Moscow (Okhotny Ryad / Teatralnaya / Chekhovskaya / Pushkinskaya)
- Hybrid schedule (not fully remote); your future colleague lives in Moscow
- Final compensation depends on your experience, plus profit sharing
- Salary paid in stablecoins
About Reinforce
Reinforce.fi helps businesses in emerging markets earn more on idle USDT (TRC20) — without DeFi complexity and without locking liquidity.
- Higher yield (up to ~2× vs standard options) on USDT that would otherwise sit idle
- Full transparency and simple withdrawals at any time
- At the core — our own reinforcement-learning strategies, with automated management and capital reallocation 24/7
(ex-team Overnight.fi)
How to apply
Email your CV and a short note on relevant experience to [email protected], naming the role you are applying for. If your experience fits, there will be a small test task.