Dolat Capital - Quantitative Developer - Artificial Intelligence Machine Learning

Who We Are

At Dolat Capital, were a team of traders, tech enthusiasts, and problem solvers driven by a passion for markets and innovation. We specialize in ultra-low latency market-making and active trading across Equities, Futures, and Options. With top-tier fill rates and cutting-edge technology, we thrive where finance meets :

• Quant Trading & Strategy Design and optimize high-performance strategies for derivatives, options, and ETFs. Monitor PnL and Sharpe ratios (6+), while actively identifying market inefficiencies in real time.
• Trading Systems Development Build low-latency, high-throughput systems and simulation tools. Focus on fast execution, real-time risk, and performance tracking.
• Algo & Quant Analysis Use statistical methods and large-scale HFT data (Python/C++) to validate and refine strategies in live environments.
• AI/ML Integration Develop AI/ML models for signal detection, alpha generation, and market prediction using large datasets.
• System & Network Optimization Enhance system performance with deep expertise in concurrent programming, TCP/UDP, and network protocols.
• Collaboration & Mentorship Work closely with traders, engineers, and data scientists. Represent Dolat in tech mentorship and campus events.
  
  

• Education: B.Tech in Computer Science/IT and a masters degree in computer science or computational finance.
• Strong grasp of data structures, algorithms, and object-oriented programming (C++).
• 1-2 years of experience.
• Proficient in Python and C++, with hands-on experience in Linux systems programming.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with distributed systems and high-concurrency architectures.
• Solid understanding of network programming, including TCP/UDP protocols.
• Excellent analytical and problem-solving abilities, with a passion for technology-driven innovation in financial markets.