Research Engineer - Numerical Programming & HPC

[Recruiter-Jim]

Are you a skilled numerical programmer with a passion for high-performance computing and simulation engineering?

A leading high-frequency algorithmic trading firm in NYC is looking for a talented Research Engineer to join their quantitative research team. You'll play a key role in developing and scaling simulations, implementing quantitative models, and optimizing research infrastructure for maximum performance.

What You'll Do:

• Simulation Infrastructure:
  • Design, develop, and maintain a high-performance simulation infrastructure using C++ for backtesting and evaluating trading strategies.
  • Leverage cutting-edge HPC techniques, including CUDA and a cluster of Nvidia A100 Tensor Core GPUs, to scale simulations and handle massive datasets and complex scenarios efficiently.
• Quantitative Modeling:
  • Implement and optimize sophisticated quantitative models in C++, ensuring accuracy, efficiency, and adherence to research specifications.
  • Apply advanced scheduling techniques like task graphs, dependency analysis, dynamic scheduling, priority queues, and load balancing to maximize performance and resource utilization.
• Market Data Integration:
  • Onboard and parse market data from various exchanges, meticulously accounting for exchange-specific quirks and data formats.
• Collaboration & Research:
  • Collaborate closely with quant researchers to translate complex research ideas and mathematical models into efficient, scalable, and production-ready code.
  • Actively participate in research discussions, contribute to code reviews, and share expertise in HPC and optimization techniques.

What You'll Need:

• • Expert C++ Programming: This is the foundation. You'll need deep knowledge of C++, including advanced concepts like memory management, object-oriented programming, and design patterns.
  • High-Performance Computing (HPC):
    • CUDA: Essential for harnessing the power of GPUs. You'll need to write efficient CUDA kernels and optimize code for parallel execution.
      Parallel Programming: Understanding of parallel programming concepts and techniques, including multi-threading, distributed computing, and synchronization.
      HPC Frameworks: Familiarity with MPI or other HPC frameworks for managing distributed computations.
  • Numerical Methods and Libraries: Strong grasp of numerical methods for solving mathematical problems, and experience with relevant libraries (e.g., BLAS, LAPACK).
  • Scheduling and Optimization: Knowledge of task scheduling algorithms, dependency analysis, and optimization techniques for maximizing performance and resource utilization.
  • Data Analysis: Ability to work with large datasets, perform statistical analysis, and interpret results.
  • Market Data Handling: Experience with onboarding, parsing, and normalizing market data from various exchanges, including handling exchange-specific quirks.
• Soft Skills:
  • Collaboration: Ability to work effectively with quant researchers, understand their needs, and translate their ideas into code.
  • Communication: Clearly communicate technical ideas and findings to both technical and non-technical audiences.
  • Problem-solving: Strong analytical and problem-solving skills to tackle complex challenges in simulation, optimization, and data analysis.
  • Adaptability: Ability to learn new technologies and adapt to evolving research needs.
• Bonus Skills:
  • Financial Markets Knowledge: Understanding of financial instruments, trading strategies, and risk management.
  • Machine Learning: Familiarity with machine learning techniques for building predictive models.
  • Cloud Computing: Experience with cloud platforms (AWS, GCP) for scaling simulations and managing data.

The team are indexing for a smart junior (Around 3-5 YOE).
Comp? Around $400k 1st year all in.