Top Tech Jobs & Startup Jobs in Chennai

Designs, develops, and maintains scalable software solutions integrating AI and machine learning models into commercial products and internal processes. Collaborates with data scientists, product managers, and cross-functional stakeholders; writes high-quality code; reviews architectures; supports product launches and process improvements; and follows Agile, NPI, and deployment best practices.

Designs and tests low- and medium-voltage industrial drive systems, power electronics, control cabinets, protection circuits, and related hardware. Responsibilities include sizing, modeling, simulations, loss calculations, documentation, prototype validation, manufacturing support, factory acceptance testing, and compliance with UL/IEC standards. The engineer collaborates with project teams and may travel occasionally to commission engineered projects.

Designs, builds, delivers, and maintains software applications and services across machine, cloud, platform, and application environments. Responsibilities include requirements analysis, coding, testing, documentation, performance assessment, SDLC activities, CI, Agile development, and applying data structures and algorithms. The role requires experience with C#, Python, web technologies, React or Angular, Windows, PowerShell, networking, relational databases, and software security practices.

Design, develop, deploy, and integrate AI, machine learning, and generative AI solutions for industrial and business applications. Own the machine learning lifecycle, define architectures, assess data readiness, monitor production models, and ensure reliability and maintainability. Evaluate emerging AI technologies, manage technical delivery from partners and contractors, and collaborate with cross-functional stakeholders to identify use cases, support adoption, and deliver measurable operational improvements.

Designs, develops, deploys, and integrates AI, machine learning, deep learning, and generative AI solutions for industrial and business applications. Owns the machine learning lifecycle, solution architecture, data strategy, model monitoring, and production integration. Evaluates emerging technologies, manages technical delivery from partners and contractors, and collaborates with cross-functional teams to deliver scalable, reliable, and maintainable AI solutions.

Design and deliver production-ready AI, machine learning, and generative AI solutions for industrial and business challenges. Own the ML lifecycle, architecture, data strategy, deployment, monitoring, and integration across cloud and on-premises environments. Evaluate emerging technologies, guide internal and external partners, define technical requirements, and support adoption through documentation, training, and cross-functional collaboration.

Designs, develops, deploys, and integrates AI, machine learning, generative AI, and analytics solutions for industrial and business challenges. Owns the machine learning lifecycle, solution architecture, data strategy, production integration, monitoring, and technical evaluation of internal and external partners. Collaborates with cross-functional stakeholders, supports adoption, evaluates emerging AI technologies, and develops solutions such as predictive maintenance, anomaly detection, forecasting, document analysis, and knowledge tools.

Designs, develops, deploys, and integrates AI, machine learning, deep learning, and generative AI solutions for industrial and business challenges. Responsibilities include selecting modeling approaches, managing the ML lifecycle, defining solution architectures, analyzing operational data, supporting production deployment and monitoring, managing technical partners, and ensuring data governance, reliability, and maintainability. The role also evaluates emerging technologies, collaborates across functions, and supports user adoption and continuous innovation.

Designs, develops, deploys, and integrates AI, machine learning, generative AI, and optimization solutions for industrial and business applications. Owns the machine learning lifecycle, solution architecture, data strategy, model monitoring, and production readiness. Evaluates technologies, manages technical delivery from vendors and contractors, and collaborates with cross-functional teams to translate operational needs into scalable AI tools. Supports adoption, innovation, governance, and continuous improvement across energy and industrial environments.

Develop and execute validation strategies, automated tests, test rigs, regression testing, and defect analysis for GE embedded control platforms and industrial communication systems. Build Python test scripts and embedded software, including drivers and IEC 61850 tools. Support hardware and software validation, product releases, customer issue resolution, laboratory management, documentation, and cross-functional global collaboration across power, marine, metals, and oil and gas domains.