AI Engineer

Dr. Reddy’s Laboratories Ltd. is a leading multinational pharmaceutical company based across global locations. Each of our 24,000 plus employees comes to work every day for one collective purpose: to accelerate access to affordable and innovative medicines because Good Health Can’t Wait.

We started in 1984 with a modest investment, 20 employees and a bold vision. Today, we have research and development centres, manufacturing facilities or a commercial presence in 66 countries.

For nearly four decades, we have stood for access, affordability and innovation based on the bedrock of deep science, progressive people practices and robust corporate governance. As the pharmaceutical industry evolves and undergoes disruption, we see an opportunity – to strengthen our core further (the next steps) and to build the future (the new bets).

‘The Next and the New’ is how we aim to continue to be the partner of choice – purpose-driven, future-ready and sustainable.  Our aim is to reach over 1.5 Bn+ patients across the world by 2030 by growing our core businesses and building for the future with sustainability at the core of our purpose and strategy. Sustainability for us means operating in a manner that respects people, planet and purpose – helping us conserve precious resources, serve our patients, create value for stakeholders, give back to society, fulfil our potential and maintain our integrity and transparency

Dr Reddy’s maintains a work environment, free from discrimination and is an equal opportunity employer. We are committed to employ & nurture all qualified diverse workforce without regard to race, colour religion, nationality, sex, age, disability status, genetics, sexual orientation, gender expression, citizenship or any other characteristic or classification protected by applicable law(s) of the country we operate in. We treasure every talent, and recognize merit and diversity in our organization.

Role Summary

We are seeking an AI/ML Engineer with ~5–6 years of experience to develop and manage the generative AI models that power our OCM platform. In this role, you will develop and maintain AI pipelines for content generation and evaluation, working with state-of-the-art ML tools. You will ensure our AI models produce high-quality, multilingual content and continuously improve through feedback loops.

Responsibilities

•Design and implement end-to-end generative AI pipelines for creating personalized marketing content. This includes data preprocessing, model inference, and post-processing of outputs for quality assurance.

•Leverage pre-trained models (e.g., via Azure OpenAI or Hugging Face models) and customize them for the domain needs.

•Create mechanisms to automatically score or classify generated content for relevance, quality, and compliance. Implement evaluation workflows to filter out inappropriate or low-quality AI-generated content before it reaches end-users.

•Incorporate feedback from users and domain experts into the model improvement process. For example, implement prompt adjustments, model retraining, or rules based on what content performs best, to continuously refine output.

•Ensure the AI pipeline can generate content in multiple languages. Adapt models or use translation services as needed so content stays accurate and contextually appropriate across languages.

•Deploy models and AI services into production (using Azure services like Azure Functions or container deployments). Monitor model performance (latency, accuracy) and optimize as required. Troubleshoot and resolve issues in model inference in production environments.

•Work closely with the cross functional teams to develop AI capabilities into the application.

•Stay updated with the latest developments in AI/ML (new models, techniques, prompt engineering strategies) and experiment with improvements that could enhance our product’s intelligence and efficiency.

•Document model architectures, experiment results, and maintain version control for models and data (ensure we know which model version is in production). Follow best practices for model lifecycle management.

Required Skills

•5–6 years in AI/ML engineering or applied data science, with hands-on experience in building and deploying machine learning models.

•Strong proficiency in Python and deep learning frameworks.

•Experience with generative models (Transformers, GPT-based models like GPT-Image-1, GPT-4o etc or similar) is essential.

•Familiarity with th…