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GenAI Developer 2 (Pune Division)

Atlas Copco Group · Pune

📅 14/08/2026
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Our solutions are a key part of most industries - electronics, medical research, renewable energy, food production, infrastructure and many more. Working with us means working with the latest technologies and groundbreaking, sustainable innovations. Join us on our journey for a better tomorrow. Your Role We are looking for a Data Scientist with 5-7 years of experience who has hands-on expertise in building and deploying classical machine learning and deep learning models, along with exposure to Generative AI systems. You will collaborate with business and engineering teams to translate operational challenges into AI/ML problem statements and contribute to scalable solutions that can be deployed on cloud infrastructure. Main Responsibilities - Work with business stakeholders to understand problems and help frame them into AI/ML use cases. - Design and implement models using classical techniques (regression, classification, forecasting, anomaly detection) and deep learning architectures (CNNs, Transformers). - Contribute to Generative AI applications such as RAG pipelines, agentic frameworks, and LLM orchestration. - Support responsible use of GenAI by evaluating model suitability, explainability, and cost-effectiveness. - Assist in setting up CI/CD pipelines for model training, testing, and deployment; monitor models for data drift and performance issues. - Design, develop, implement and support GenAI platforms, solutions and systems from scratch and integrate GenAI technology into existing platforms and applications securely and stably. - Write and maintain documentation for GenAI solutions, including technical specifications, user guides and best practices. - Work closely with cross-functional teams and stakeholders to understand requirements and identify opportunities for GenAI Solutions, as well as to ensure successful deployments. - Stay updated on the latest advancements in GenAI technology and contribute to the research and development of current AI-based solu .
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