remote protocol/engineering/dai

Who are we?

We are building a delta edge neutral trading protocol that captures volatility and return across liquid BTC, ETH, and altcoins through advanced foundation trading, OTC liquidity strategies, and perpetual derivatives. By combining market neutral strategies with innovative hedging solutions, we offer unparalleled capital efficiency for institutional and advanced traders.

Our team brings deep experience from leading crypto protocols, traditional finance companies, and exchanges, backed by top-tier investors and partners. We create the next generation of trading infrastructure optimized for digital asset markets.

What we are building

We desire a neutral, volatility-based trading infrastructure designed to enable scalable exposure to key digital assets while managing trend risk. Our protocol integrates:

• Delta Neutral Strategies: Utilize basis trades, financing rate arbitrage, and hedging for consistent return and market recognition
• OTC Integration: Obtain discounted assets to improve cost and arbitrage opportunities
• Automated hedging: Combining perpetual futures, options and liquidity strategies to minimize risk

This platform is designed for institutions, treasuries and complex market participants looking for capital-efficient returns in the crypto space.

Role summary

We draw on quantitative research to drive fundamental research into market microstructure, order book dynamics, and predictive modeling across multiple asset classes. You will design and validate new statistical and automated learning models, build research pipelines, and develop strategies ranging from cross-market arbitrage to high-frequency trading. You’ll analyze massive amounts of tick-level data, perform rigorous testing and simulation, and collaborate with engineers and traders to bring cutting-edge research into live production systems.

Key responsibilities

Research and development

• Conduct fundamental research into market microstructure, order book dynamics, and price formation mechanisms across multiple asset classes
• Design and validate new mathematical models for predictive quantitative trading, with an emphasis on theoretical rigor and experimental verification
• Develop statistical arbitrage strategies through extensive research into cross-market correlations and inefficiencies
• New approaches to signal generation using advanced statistical techniques, with time horizons from microseconds to minutes
• Conduct comprehensive simulation and simulation studies to validate trading hypotheses across diverse market conditions

Data analysis and modeling

• Analyze petabytes of historical market data at the tick level to identify precise microstructural patterns and trading opportunities
• Build sophisticated market simulators for both liquid and illiquid assets, featuring realistic market impact models
• Develop machine learning research pipelines for feature engineering and training models at scale
• Implement advanced time series analysis and signal processing techniques

Qualifications

necessary

• Advanced degree (MS/PHD preferred) in mathematics, statistics, computer science, physics, or related quantitative field
• Expert-level Python programming skills for quantitative research, including:
  • Advanced Numpy/pandas for large-scale data processing
  • Scientific computing with Scipy, StatsModels and specialized libraries
  • Deep Learning Frameworks (Pytorch, TensorFlow, Jax)
  • Optimization and performance improvement techniques
• A strong foundation in probability theory, stochastic calculus, and statistical inference
• Experience with parallel computing and distributed data processing (Dask, Ray, Pyspark)

Research focus

• Experience developing and deploying new trading algorithms or market microstructure research
• Proficiency in machine learning techniques including deep learning, reinforcement learning, and online learning algorithms
• Strong background in numerical methods, optimization theory and computational mathematics
• Experience with Python-based research tools:
  • jupyter/ipython for interactive search
  • matplotlib/plotly/seaborn for advanced visualization
  • Cython/numba for performance-critical components
• Proven track record of building comprehensive research pipelines from hypothesis generation to production publication

Quantitative trading

• Proven experience in developing a high-frequency trading strategy with a pronounced PNL effect
• Deep understanding of market making, inventory management and adverse selection models
• Experience with order book rebuilding and tag data analysis

Nice to have

• Experience with Rust programming and ability to integrate Python research into Rust-based production systems
• Knowledge of Python interoperability (PYO3, Malin)
• Experience porting research models from Python to low-profile Rust applications
• Understand the rust memory model and performance characteristics of system integration

Technical environment

• Protolanguage: Python for research, prototyping, and market microstructure analysis
• Production Integration: Rust-based trading systems (integration experience helpful but not required)
• Infrastructure: Rust-based custom trading framework, bare metal servers, kernel bypass networking
• Data Stack: Time Series Databases, Apache Arrow/Parquet, Distributed Computing Platforms

What we offer

• Work on cutting-edge research problems at the intersection of finance, mathematics, and systems engineering
• Collaborate with a world-class team of researchers and engineers
• An opportunity to see research translated into production trading systems
• Significant independence in research direction and implementation approach
• Performance-based compensation with great earning potential

Why join us?

Neutrl Labs is transforming how institutions capture volatility and return in crypto markets. Whether you’re passionate about building cutting-edge trading algorithms or creating bulletproof infrastructure, this is your chance to make a real impact on the future of decentralized capital efficiency.

Apply now and help redefine the future of enterprise-grade Defi.