Staff Software Engineer (IC) - Quant Hedge Fund in NEW YORK CITY METROPOLITAN AREA

About the Firm:

This role is with one of the world’s most prestigious quantitative hedge funds, where data-driven decision-making and cutting-edge technology form the backbone of success. The firm specializes in leveraging advanced mathematics, statistics, and machine learning to drive global trading strategies. Engineering teams power high-performance systems that enable real-time data analysis and execution.

A Staff-Level Python Engineer in this role will be responsible for developing scalable, efficient, and innovative solutions to empower researchers, analysts, and traders in high-stakes financial markets.

Key Responsibilities:

1. Core Development & Optimization

• Designs, implements, and maintains high-performance Python-based systems for data ingestion, analysis, and real-time decision-making.
• Develops robust APIs and frameworks to empower quantitative researchers and traders.
• Optimizes existing Python code for scalability, low latency, and high throughput in both real-time and batch environments.

2. Collaboration & Leadership

• Partners with cross-disciplinary teams, including quant researchers, data scientists, and portfolio managers, to translate business and research needs into technical solutions.
• Provides technical mentorship to junior engineers and ensures best practices in code quality, testing, and deployment.

3. Systems Integration

• Integrates Python applications with distributed computing systems, trading platforms, and other critical infrastructure.
• Collaborates with DevOps teams to ensure system reliability, security, and performance.

4. Innovation & Problem Solving

• Explores new technologies and methodologies to enhance computational and operational capabilities.
• Identifies and mitigates risks in system design, ensuring fault-tolerant and highly available systems.

Qualifications:

Required:

• 8+ years of software engineering experience, with a significant focus on Python development in performance-critical applications.
• Proven expertise in building distributed, scalable systems and handling large datasets in real-time.
• Strong knowledge of data structures, algorithms, and multithreading.
• Hands-on experience with SQL and NoSQL databases for both OLTP and OLAP workloads.
• Solid understanding of cloud-native technologies and containerized environments (e.g., AWS, GCP, Kubernetes).
• Demonstrated ability to debug complex systems and tackle performance bottlenecks.
• A Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.

Preferred:

• Previous experience in a quant finance environment or other high-performance industries (e.g., gaming, aerospace).
• Knowledge of C++ or Java for system-level programming and integration.
• Familiarity with quantitative modeling tools, machine learning libraries (e.g., TensorFlow, PyTorch), or statistics packages (e.g., NumPy, SciPy, pandas).
• Experience with time-series databases and real-time streaming platforms (e.g., Kafka, Flink).
• Understanding of market microstructure, trading systems, and financial instruments.

What the Role Offers:

• An opportunity to work with some of the brightest minds in finance and technology.
• Access to cutting-edge tools and platforms to solve complex problems.
• A culture of innovation, collaboration, and continuous learning.
• Highly competitive compensation packages, including performance-driven bonuses and equity options.
• Generous benefits, including health insurance, wellness programs, and relocation assistance.