About Us: Join a leading hedge fund at the forefront of quantitative finance, where cutting-edge technology and advanced analytics drive innovative trading strategies. We are seeking an HPC Simulation Engineer to design, develop, and optimize simulation frameworks and distributed systems. This hands-on role provides an opportunity to leverage the full scientific stack in Python while contributing to high-performance computing solutions in a collaborative, fast-paced environment.
Key Responsibilities:
Simulation Development:
Design and implement advanced simulation frameworks tailored to complex financial modeling and algorithmic strategies.
Develop robust, scalable, and efficient codebases using Python and its scientific ecosystem (NumPy, SciPy, pandas, etc.).
Optimize performance-critical components for large-scale computations.
Distributed Systems:
Build and maintain distributed computing systems to handle large-scale simulations.
Leverage tools such as MPI, Dask, and Ray to implement parallelized workflows.
Collaborate with infrastructure teams to ensure high availability and low-latency performance.
Collaboration:
Work closely with quantitative researchers, data scientists, and other engineers to translate requirements into actionable development goals.
Participate in cross-functional code reviews and architectural discussions to drive best practices.
Contribute to the development of reusable libraries and tools that enhance productivity.
Innovation and Strategy:
Stay updated on advancements in high-performance computing, distributed systems, and financial simulations.
Identify opportunities for process and technology improvements to enhance system capabilities.
Participate in defining long-term strategies for simulation platforms and related infrastructure.
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Computational Physics, Applied Mathematics, or a related field.
5+ years of experience in high-performance computing, distributed systems, or simulation engineering.
Strong proficiency in Python, including the full scientific stack (NumPy, SciPy, pandas, matplotlib, etc.).
Hands-on experience with distributed computing frameworks such as MPI, Dask, or Ray.
Proven ability to design and optimize algorithms for performance and scalability.
Familiarity with Linux environments and shell scripting.
Preferred Qualifications:
Experience in financial modeling, quantitative research, or algorithmic trading.
Background in GPU programming (CUDA) or hardware acceleration techniques.
Knowledge of database systems, particularly time-series databases.
Soft Skills:
Strong problem-solving abilities and analytical thinking.
Clear and concise communication skills, both written and verbal.
A collaborative mindset with the ability to work effectively in a multidisciplinary team.
Why Join Us?
Work on challenging problems with a team of world-class professionals.
Engage in a culture of innovation and excellence, where your contributions directly impact performance.
Competitive compensation and benefits package, including ongoing professional development.
Be part of a prestigious firm driving the future of quantitative finance.