Ml Platform Engineer in Gurugram

About Us: Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at saucelabs.com . The Role: We are seeking an innovative and experienced AI Architect to join our engineering leadership team. This is a strategic role that will be instrumental in designing and building the next generation of AI-powered features for our continuous testing platform. You will be responsible for architecting scalable and robust AI solutions that transform how our customers gain insights from their test data and production environments, and how they create tests. Responsibilities: Define AI Architecture: Lead the design and architecture of cutting-edge AI/ML solutions for new product offerings, ensuring scalability, performance, quality and reliability within a cloud-native environment. AI-Powered Insights (Test & Production): Architect AI systems to derive actionable insights from vast quantities of test run logs and analytics data. This includes identifying patterns, anomalies, and performance trends. Production Error Reporting Integration: Design AI solutions that integrate with our existing error reporting product to analyze production issues for mobile and web applications, providing deeper understanding and predictive capabilities. Unified Data Intelligence: Develop architectures for combining insights from both test runs and production data, creating a holistic view of application quality and user experience. Automated Failure Analysis & Remediation: Architect AI models and systems t

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist II Role Overview Build and productionize enterprise-grade AI and Generative AI solutions for Mastercard. This role combines strong software engineering with model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps. Key Responsibilities Design, develop, test, and maintain scalable AI/ML applications, APIs, and reusable engineering components. Fine-tune and evaluate foundation models using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning. Build RAG solutions, embeddings workflows, vector-search applications, and AI agents. Create end-to-end ML pipelines for data preparation, training, evaluation, deployment, monitoring, and retraining. Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving for governed model development and operations. Implement CI/CD, automated testing, observability, model monitoring, and production support practices. Partner with data science, engineering, product, security, privacy, and governance teams to deliver reliable and responsible AI solutions. Required Skills & Experience 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field. Strong Python, SQL, object-or

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