Specialist AI Engineer

Role Summary

We are seeking an AI/ML Engineer with 56 years of experience to develop and manage the generative AI models that power our OCM 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 products 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.

Qualifications :

Required Skills

56 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 the Hugging Face ecosystem (libraries like Transformers datasets). Experience with DSPy or other AI orchestration frameworks is a plus.

Experience using cloud AI services particularly Azure OpenAI Service and Azure Cognitive Services to leverage large language models and other AI capabilities.

Understanding of RAG and vector databases (e.g. pgvector Pinecone etc.) and how to use them for storing embeddings or enabling semantic search.

Ability to build or utilize APIs (using Python FastAPI or Flask) to serve AI model functionality.

Experience in prompt engineering crafting and refining prompts to get better AI output and fine-tuning models for improved performance.

Understanding of active learning or feedback loop mechanisms to improve models over time.

Prior experience deploying ML models in a production environment. Comfortable with best practices for scaling ML services monitoring (logging performance tracking) and troubleshooting live issues.

Excellent analytical skills to diagnose issues with model output or data. Ability to experiment methodically and come up with creative solutions in an emerging field.

Good to Have

Familiarity with content validation against guidelines or compliance requirements (e.g. understanding of medical legal regulatory checks for marketing content). Experience with LMRC or similar review processes is a plus.

Some knowledge of data pipelines ETL or data preprocessing techniques especially for unstructured data (Especially Image data).

Interest or background in healthcare or marketing technology. Understanding the unique challenges of healthcare marketing (such as privacy or compliance) can help in building better AI solutions.

Experience with ML lifecycle tools (MLflow Kubeflow) or experiment tracking and familiarity with DevOps for ML (CI/CD for model deployment)are nice to have.

Additional Information :

About the Department
Digital Process and Excellence (DPEx)
Our digital transformation journey is led by the DPEx team and is structured along the lines of Digitalize the Core and Transform with Digital.
With a mandate to ensure continuous process improvement and drive patient centric innovation it spans all functions and other words you could be working on projects to expedite research outcomes one day designing customer engagement platforms the next and simplifying warehouse processes the third.
Some its priorities are:
Reimagine Dr. Reddys as a platform-based organization.
Create Data as an asset that brings competitive advantage and business impact.
Create Digital solutions that make the lives of our patients and customers easier and better.

Benefits Offered
At Dr. Reddys we actively help to catalyse your career growth and professional development through personalised learning programs.
The benefits you will enjoy at Dr. Reddys are on par with the best industry standards. They include among other things and other essential equipment joining & relocation support family support (Maternity & Paternity benefits) learning and development opportunities medical coverage for yourself and your family life coverage for yourself.

Our Work Culture
Ask any employee at Dr. Reddys why they come to work every day and theyll say because Good Health Cant Wait. This is our credo as well as the guiding principle behind all our actions. We see healthcare solutions not only as scientific formulations but as a means to help patients lead healthier lives and were always attuned to the new and the next to empower people to stay fit. And to do this we foster a culture of empathy and dynamism. People are at the core of our journey over the last few decades. They have been supported by an enabling environment that buoys individual ability while fostering teamwork and shared success. We believe that when people with diverse skills are bound together by a common purpose and value system they can make magic.
For more details please visit our career website at Work :

No

Employment Type :

Full-time