hirix is a recruitment partner for finding IT talent. We help companies build strong teams and specialists find projects where their expertise is truly needed. We recruit in IT, Digital, AI and guide each candidate from the first contact to the offer.
Our client is expanding their team and is looking for a Senior Quant/ML Researcher.
About the project and team:
A technology company developing quantitative infrastructure and ML solutions for digital asset markets. The project is in the pre-launch stage, and the team specializes in quant research, machine learning, and blockchain development.
Responsibilities in this role:
- Full research cycle on short-term microstructure, LP/hedging, execution, inter-venue signals, risk distribution, and related crypto/DeFi tasks;
- Research design: hypothesis, target/labeling, baseline, metrics, causally correct OOS testing, regime analysis, and explicit GO/NO-GO criteria;
- Data work: source identification, time alignment, quality control, feature engineering, and reproducible data contracts;
- ML/DL based on task structure; RL or other sequential control methods — only when truly justified;
- Realistic simulation and trading economics: commissions, slippage, liquidity, latency, adverse selection, impact, fill assumptions, hedging, and DEX/CEX synchronization;
- Paper/shadow strategies, sim-to-real analysis, and collaboration with quant developers when transferring proven solutions to production;
- Engineering standard of research: reproducible experiments, clean Python, critical checks, monitoring, and disciplined use of LLMs/agents.
Candidate Expectations:
- Verifiable experience in 2–3 Quant/ML projects where you were personally responsible for a significant part of the chain from problem definition and data to testing, code, and the decision to implement or GO/NO-GO;
- Excellent Python and strong engineering foundation: you write, debug, and review research code yourself;
- Strong statistics, probability, optimization, and time series analysis: temporal dependency, leakage, selection bias, uncertainty, and honest OOS testing;
- Deep practical understanding of microstructure and execution: order book/flow, liquidity, latency, fees, slippage, adverse selection, impact, sizing, and hedging;
- Strong practical proficiency in ML/DL for sequential financial data and the ability to distinguish real signal from metric optimization;
- High degree of autonomy: structure an unclear problem, choose the most informative experiment, quickly stop weak hypotheses, and make decisions based on evidence;
- Working understanding of crypto market structure. Direct DeFi/DEX experience will be a plus, but strong CEX/microstructure experience can compensate for it with rapid adaptation.
Conditions and Opportunities:
- Full-time employment, 5/2, hybrid/remote format, office in the center of Moscow;
- Work with real capital where research quality, execution realism, and risk control are directly relevant;
- Direct collaboration with Quant/ML, development, and company leadership, high autonomy, and short feedback loops;
- Small team where strong research can become a production system, not just end with a presentation;
- Compensation for all necessary tools and software for work.
