Senior ML Engineer: Real-Time Trading Models

Rapidtrade; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Rapidtrade is seeking a Senior Machine Learning Engineer to join its AI team and build the next generation of predictive trading models. You will work on time-series forecasting, reinforcement learning, and large-scale data processing in a fast-paced fintech environment.

You will design ML models for market prediction, deploy pipelines across billions of data points daily, and collaborate with analysts to translate trading strategies into robust ML systems, with sub-millisecond latency goals.

Qualifications

• 5+ years of experience in machine learning or related field.
• Strong background in Python, with experience in PyTorch or TensorFlow.
• Experience with time-series analysis and forecasting.
• Familiarity with distributed computing (Spark, Ray, or similar).
• MS or PhD in Computer Science, Machine Learning, or related field.
• Track record of deploying ML models to production.

Responsibilities

• Design and implement machine learning models for market prediction and risk assessment.
• Build and maintain scalable ML pipelines processing billions of data points daily.
• Collaborate with quantitative analysts to translate trading strategies into ML systems.
• Optimize model inference for sub-millisecond latency requirements.
• Mentor junior engineers and contribute to engineering best practices.
• Research and evaluate new ML techniques and frameworks.

Skills

Python

PyTorch

TensorFlow

Time-series analysis

Forecasting

Distributed computing

Spark

Ray

Education

MS/PhD in CS or ML

Tools

Spark

Ray

Job description

Rapidtrade is seeking a Senior Machine Learning Engineer to join its AI team and build the next generation of predictive trading models. You will work on time-series forecasting, reinforcement learning, and large-scale data processing in a fast-paced fintech environment.

You will design ML models for market prediction, deploy pipelines across billions of data points daily, and collaborate with analysts to translate trading strategies into robust ML systems, with sub-millisecond latency goals.