Low-Latency Quant Trading Engineer - Go & Python

Getmidas; Fatih; On-site; TRY 600,000 - 1,200,000; Full time

Job summary

Midas is seeking exceptional engineers to design and build high-throughput, low-latency trading systems across crypto exchanges and liquidity venues. You will own the full lifecycle from research and backtesting to live deployment, monitoring, and optimization.

You should thrive in high-stakes environments, have strong Go and Python skills, and a deep understanding of market microstructure, latency, and risk management in 24/7 markets.

Qualifications

• Strong fundamentals in computer science and quantitative problem solving.
• Hands-on experience building quantitative trading, algorithmic trading, execution, or HFT systems.
• Deep understanding of market microstructure, order books, execution, slippage, and liquidity.
• Experience with execution algorithms, netting, dynamic or delta hedging, and inventory management.

Responsibilities

• Own the full lifecycle: from quantitative research, backtesting, and simulation to implementation, deployment, monitoring, and live performance tuning.
• Design, build, and optimize automated execution and hedging systems operating across crypto exchanges and liquidity venues.
• Develop execution algorithms, netting mechanisms, and dynamic hedging strategies to manage trade flow and market exposure.
• Build systems to manage, rebalance, and risk-manage inventory positions resulting from trading and execution activity.

Skills

Go (Golang)

Python

Quantitative trading

Market microstructure

Distributed systems

Ownership mindset

Tools

REST/WebSocket APIs

Real-time market data

Job description

Midas is seeking exceptional engineers to design and build high-throughput, low-latency trading systems across crypto exchanges and liquidity venues. You will own the full lifecycle from research and backtesting to live deployment, monitoring, and optimization.

You should thrive in high-stakes environments, have strong Go and Python skills, and a deep understanding of market microstructure, latency, and risk management in 24/7 markets.