Senior AI Engineer, Quant Trading Systems

Entec Partners; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Entec Partners is seeking a Senior AI Engineer to design and deploy advanced ML models for automated trading across asset classes. You will collaborate with researchers, quants, and infra engineers to translate mathematics into production-ready systems.

The role emphasizes low-latency processing, building robust data pipelines, backtesting, and staying at the cutting edge of AI/ML research with real-time market data.

Qualifications

• Advanced degree in a quantitative field (CS/ML/Stats/Math).
• Strong Python programming with ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Experience with high-performance computing and optimization techniques.
• Knowledge of financial markets and trading concepts across asset classes.
• Experience with C++ for performance-critical components.
• Background in signal processing, NLP, or computer vision.
• Experience with cloud-based ML infrastructure and containerization.

Responsibilities

• Develop and implement ML models to analyze market data, detect patterns, and generate trading signals.
• Design and build data pipelines for processing large volumes of market data.
• Optimize algorithms for low-latency execution in production trading systems.
• Conduct rigorous backtesting and performance analysis of AI-driven trading strategies.
• Stay current with latest developments in AI/ML research and assess applicability to trading.
• Contribute to the firm's ML infrastructure and tooling.

Skills

Python

Machine Learning

ML frameworks

Education

Advanced degree in Computer Science / ML / Statistics / Mathematics

Tools

PyTorch

TensorFlow

scikit-learn

C++

Job description

Entec Partners is seeking a Senior AI Engineer to design and deploy advanced ML models for automated trading across asset classes. You will collaborate with researchers, quants, and infra engineers to translate mathematics into production-ready systems.

The role emphasizes low-latency processing, building robust data pipelines, backtesting, and staying at the cutting edge of AI/ML research with real-time market data.