Website:
rozarioglobal.com
Job details:
About Rozario Global Management LLC Rozario Global Management is a US-based, SEC-Exempt Reporting Adviser (ERA) operating a highly sophisticated quantitative trading and investment firm. We do not rely on discretionary forecasting; we rely on math, market microstructure, and raw computational power. We combine machine learning, data science, and heavy quantitative research to systematically extract absolute alpha from global equity and derivative markets.
Our core engineering pod builds the architecture that makes this possible. We are currently scaling the Similize® engine—a proprietary, low-latency execution and algorithmic scoring ecosystem (DAL 2.0). This infrastructure powers everything from large-scale distributed model training (via Ray) to high-frequency signal generation across a vast array of statistical arbitrage techniques.
The Role We are seeking an elite Quantitative Software Engineer based in India to join our core U.S. engineering team. This is not a standard back-office IT role; this is a mandate to deliver world-class AI/ML capabilities and build the mission-critical infrastructure that directly drives our live trading activities.
Working in a highly secure, modular development environment, you will be tasked with transforming localized quantitative research into institutional-scale production code.
Primary Responsibilities:
- Systems Architecture: Design, build, and optimize the low-latency pipelines (Python, MinIO/S3, IBKR APIs) that power our data ingestion, research environments, and live algorithmic execution.
- Model Development & Deployment: Prototype, backtest, and implement machine learning and statistical models designed to identify pricing inefficiencies across our trading ecosystem.
- Domain Authority: Serve as a technical leader for the systems underpinning our machine learning and quantitative algorithms, scaling these components from localized testing to distributed, live-market environments.
- Quantitative Tooling: Architect the internal frameworks and computational libraries our firm uses to conduct research, with a ruthless focus on performance optimization, execution latency, and scalability.
Qualifications & Technical Mastery:
- Education: BS or MS in Computer Science, Applied Mathematics, Physics, or a strictly related highly technical field from a top-tier university (e.g., IITs, NITs, BITS, or equivalent elite global institutions).
- Experience: Minimum 1 year of high-impact production experience; 3–10 years of professional software engineering experience strongly preferred.
- Computational Fluency: Deep, production-level expertise in Python. Hands-on mastery of scientific computing and ML libraries (NumPy, SciPy, Pandas, scikit-learn, Ray).
- Systems Engineering: Proven background in building large-scale, real-time, distributed data applications and working with API integrations.
- Domain Agnostic: Professional experience in quantitative finance is not required. We are seeking raw computational talent and rigorous engineering discipline. If you can build scalable, fault-tolerant mathematical systems, we will teach you the finance.
Compensation & Perks:
- Base Salary: Highly competitive and commensurate with top-tier technical proficiency and local geographic market standards.
- The Alpha Trajectory: This is a ground-floor opportunity to join the front office of an alpha-generating U.S. quantitative fund. You will gain direct exposure to Tier-1 institutional trading strategies, machine learning architectures, and complex financial systems.
- Autonomy: Fully remote flexibility with the opportunity to grow your role and compensation directly alongside the fund's scaling Assets Under Management (AUM).
Why Join Us?
This is a ground-floor opportunity to join a highly sophisticated quantitative fund. You will be exposed to Tier-1 institutional trading strategies, machine learning models, and complex financial architecture. We offer highly competitive compensation, remote flexibility, and the opportunity to grow alongside the fund's Assets Under Management (AUM).
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