About the Company 🚀

A product team at the intersection of DeFi, algorithmic trading, and ML. The team is developing a product in the stablecoin and trading strategy domain: it works with market data, explores new approaches, and implements models used in strategies.

This is not the team's first product: the previous one operated with real volumes and was profitable. The team is small, without a complex hierarchy, with direct interaction with the founder and a tight link between Quant Research, ML, and the engineering team.

Who we are looking for 🔍

A Deep Learning Researcher who has already built and launched production ML/DL models for time series and wants to apply this experience to tasks related to financial markets and trading strategies.

Experience in Quant/Trading is not required. A strong ML/DL background, experience with time series, the ability to bring models to production, and an interest in financial markets are more important.

What you will be doing ⚡

• Developing and implementing ML/DL models for time series forecasting
• Researching architectures for forecasting & sequential modeling
• Working with historical and streaming data
• Experimenting with features, architectures, and model training approaches
• Evaluating model robustness on non-stationary data
• Collaborating with the Quant Research team to apply models in trading strategies
• Analyzing how models affect strategy performance

What is important ✅

• Commercial experience of 2+ years in the role of ML Engineer / DL Engineer / ML Researcher / Data Scientist
• Experience developing production ML/DL models for time series
• Participation in the full model lifecycle: data preparation, feature engineering, training, validation, deployment, and result analysis
• Proficient Python
• Practical experience with PyTorch, Scikit-Learn, CatBoost, LightGBM/XGBoost, Optuna
• Understanding of time series, feature engineering, and model evaluation metrics
• Strong mathematical and technical foundation
• Russian language for work communication; English for reading documentation and articles

Will be a plus ➕

• Experience with reinforcement learning
• Working with market or high-frequency data
• Experience with streaming, drift, model monitoring
• Kaggle, publications, competitions, or research projects
• Personal interest in financial markets, trading, or investments
• Experience in strong ML teams

Conditions 🎁

• Hybrid format, office in the center of Moscow
• Fixed salary in stablecoins: USDT/USDC, 1:1 to USD
• Quarterly profit sharing from strategy results
• Paid vacation and flexible sick leave
• Company pays for AI subscriptions and work tools