Software Engineer Ml Infrastructure in Gurugram

Who we are Graviton Research Capital is a privately funded quantitative trading firm. We trade across a multitude of asset classes and trading venues using a diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Role Overview We are looking for a Program Manager who thrives at the intersection of rigorous engineering and predictable delivery. You will not just "manage tasks" — you will orchestrate the development lifecycle for mission-critical systems. Your goal is to ensure that our elite engineering teams can focus on high-performance code while you own the execution strategy, dependency mapping, and release discipline. Key Responsibilities Lead Agile ceremonies (Sprint Planning, Stand-ups, Retrospectives) tailored for deep-tech engineering teams. Transform high-level trading requirements into granular, executable backlogs. Own capacity planning and burn-down metrics to provide high-visibility delivery timelines. Navigate the complex interplay between engineering teams (e.g., Connectivity, Core Infrastructure, Simulation) to prevent bottlenecks. Build and maintain advanced Jira dashboards, automated roadmaps, and Confluence documentation that serve as the "single source of truth" for stakeholders. Proactively identify technical debt, architectural blockers, or resource gaps that threaten release stability. Continuously refine Agile methodologies to suit low-latency, performance-sensitive development cycles (where "Definition of Done" includes rigorous performance benchmarking). Eligibility & Required Skills 5+ years of experience as a TPM, Program Manager, or Scrum Lead in a product-engineering environment (HFT, FinTech, Networking, or Kernels/Systems). A strong grasp of the software development lifecycle for high-performance systems. While you won't write code, you must understand concepts li

Who are we: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition, to statistical inference analyzing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As part of this team you will be tasked to apply machine learning and specifically deep learning techniques to trading problems while staying connected to broader research community. The researcher will put theory into practice and can immediately impact the global trading landscape with the expanding presence of Graviton in various markets. Description Lead research in applying machine learning to a wide variety of datasets and trading problems Follow latest developments in academic research and incorporating research techniques from different fields of applications to our problems Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques Work on current and develop new deep learning models to exploit large pool of in-house features and computing infrastructure Develop scalable pipeline for building predictive models across global markets Discover and implement new sources of predictive alpha, verify that they improve existing models, and integrate them into the firm's strategy development pipeline Partner with quant researchers and software developers in implementation of conducted research to production using Python / C++ Advise infrastructure support team on latest developments on hardware and software to improve computing infrastructure for ML based research Qualifications Masters or PhD in Computer Science, Mathematics, Statistics, or a related field At least two years of demonstrated experience of ML/AI research in a professional setting or at a repu