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ML

Quantitative Developer

Very High Demand$130K – $350K+
Quantitative Developers are the engineers who turn research into production. They build the infrastructure that processes market data in real-time, trains ML models, executes trades, and monitors performance. This role requires strong software engineering skills combined with enough domain knowledge to understand what the researchers and traders need. You'll work with real-time data feeds, low-latency execution systems, containerized ML pipelines, and distributed computing. The best quant devs understand not just how to write fast code, but why certain architectural decisions matter for trading performance.
8
Core Skills
10
Key Tools
10
Lessons
6
Career Stages

A Day in the Life

“Your standup starts at 9am. The trading team reported a 50ms latency spike in the execution pipeline yesterday. You trace it to a JSON serialization bottleneck in the MT5 connector and switch to MessagePack — latency drops to 8ms. After lunch, you deploy the latest L1 model update using the blue-green deployment pipeline you built. Zero downtime. The rest of the afternoon is spent building a Grafana dashboard for the new S40 Recovery Mode metrics.”

Core Skills

1
System Architecture
2
Real-time Data Processing
3
ML Model Deployment
4
API Design
5
Database Optimization
6
Containerization
7
CI/CD Pipelines
8
Performance Optimization

Tools & Technologies

PythonC++DockerKubernetesPostgreSQLRedisFastAPITensorFlow/PyTorchGitAWS

Prerequisites

✓Strong Programming (Python/C++)
✓Data Structures & Algorithms
✓Database Design
✓API Development

Career Progression

Junior Quant Dev
→
Quant Developer
→
Senior Quant Dev
→
Lead Engineer
→
VP of Engineering
→
CTO

Curriculum

1
PYT Python for Quantitative Finance
Beginner • 50 min • Lesson 1 of 10
→
2
PIPE Data Pipelines
Intermediate • 45 min • Lesson 2 of 10
→
3
DB Database Design for Trading
Intermediate • 40 min • Lesson 3 of 10
→
4
API API Development for Trading
Intermediate • 45 min • Lesson 4 of 10
→
5
SHIP ML Model Deployment
Advanced • 50 min • Lesson 5 of 10
→
6
LIVE Real-Time Trading Systems
Advanced • 45 min • Lesson 6 of 10
→
7
DOCK Containerization & Docker
Advanced • 30 min • Lesson 7 of 10
→
8
LOGS Monitoring & Logging
Advanced • 35 min • Lesson 8 of 10
→
9
PERF Performance Optimization
Advanced • 30 min • Lesson 9 of 10
→
10
ARCH Production Architecture
Advanced • 35 min • Lesson 10 of 10
→

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