Top Tech Jobs & Startup Jobs in Chennai

Lead global MLOps delivery by designing scalable software architectures, data pipelines, and machine learning solutions. Guide architecture decisions, collaborate with research, architecture, and product teams, and coordinate software delivery. Manage and mentor developers, conduct code reviews, maintain documentation, promote engineering best practices, oversee testing and CI/CD, and remain accountable for technical debt and system quality.

Leads global market research and business projects from initiation through completion. Responsibilities include project planning, scheduling, resource and risk management, stakeholder communication, governance, reporting, KPI tracking, and continuous improvement. The role uses Smartsheet and AI tools such as Microsoft Copilot, ChatGPT, and Gemini to improve planning, documentation, reporting, automation, and decision-making while coordinating cross-functional teams and ensuring timely, high-quality delivery.

Designs and optimizes SQL Server databases, ETL/ELT pipelines, data warehouses, dimensional models, and Power BI reporting solutions. Performs data validation, query and workload optimization, pipeline monitoring, troubleshooting, and deployment activities. Partners with stakeholders to define analytics requirements and delivers dashboards, KPIs, and scalable data solutions using Azure Data Factory, Azure Data Lake Storage, DAX, and Power Query.

Leads an engineering team delivering scalable full-stack and AI-enabled products. Responsibilities include setting architecture and coding standards, improving Java APIs and Angular applications, guiding AI solution development, enforcing DevSecOps and testing practices, managing technical roadmaps, mentoring engineers, overseeing delivery, optimizing cost and performance, and evaluating emerging technologies. The role is approximately 50% leadership and 50% hands-on engineering, including architecture, coding, design reviews, and technical problem-solving.

Research, evaluate, and apply state-of-the-art ML (primarily NLP) techniques to large-scale business problems. Perform feasibility studies, EDA, and develop production-quality, scalable, reproducible ML solutions. Communicate results to stakeholders, collaborate on deployment, maintain high code and data quality, and contribute to team building and cross-functional integration.