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Answer Engine Optimization Lead in Gurugram

2 active opportunities · Updated October 2026

Explore current answer engine optimization lead jobs in Gurugram. Filter by work mode, employment type, experience, department, date posted and distance.

GR
📍 Gurugram, Haryana, India· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

Quantitative Researcher Every trading strategy begins with a question worth answering. At Graviton, we believe the best trading strategies don't come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher , you'll work on these questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies. You'll work alongside quantitative researchers and technologists in an environment where research moves quickly from an idea on a whiteboard to something that can influence live trading. The problems are open-ended. The data is enormous. The answers aren't in a textbook. You'll be expected to find them. What You'll Work On You'll work across different areas of quantitative research and systematic trading. Depending on your team and research interests, your work may include: Discovering predictive patterns and sources of alpha from billions of market events . Formulating hypotheses about market behaviour and designing experiments to test them. Applying probability, statistics, optimization and machine learning to complex research problems. Building predictive models and quantitative signals for systematic trading. Developing and improving research infrastructure that enables faster experimentation and deeper analysis. Working with large and complex datasets to uncover patterns that aren't immediately visible. Designing robust backtests and statistical tests to distinguish genuine signals from noise. Investigating market microstructure and understanding how markets behave at different timescales. Evaluating strategy performance, identifying weaknesses and continuously refining models. Working closely with technologists to translate research ideas into efficient, production-ready systems. Building AI-powered r

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GR
📍 Gurugram, Haryana, India· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

Software Engineer Build technology where every nanosecond matters. At Graviton, software isn't just a tool that supports trading. It is the infrastructure behind every research breakthrough, every trading decision and every competitive advantage. As a Software Engineer , you'll work on systems where performance, reliability and precision matter at an extraordinary scale. You'll partner closely with software engineers and quantitative researchers to build technology that processes enormous volumes of market data, powers quantitative research and supports live trading. You'll take on problems that don't have obvious answers — from designing high-performance systems and distributed infrastructure to eliminating bottlenecks measured in microseconds and building tools that make our researchers and engineers faster. Your work will go into production, be measured against real-world performance and have a direct impact on how our trading systems operate. If you enjoy solving hard engineering problems, understanding systems at a deep level and pushing technology to its limits, you'll feel right at home. What You'll Work On You'll work across the engineering stack that powers our quantitative research and trading platforms. Depending on your team, your work may include: Designing and building high-performance, low-latency systems in modern C++. Building distributed systems that process and analyze massive volumes of market data . Designing systems where latency, throughput and reliability directly influence trading performance . Working on Linux systems, networking, concurrency and multithreaded applications. Profiling systems, identifying bottlenecks and optimizing performance at the hardware and software level. Building robust infrastructure that supports quantitative research and live trading. Debugging complex production systems and solving problems where correctness and reliability are critical. Designing internal platforms and developer tools that accelerate research an

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