Overview
Lead the design, development, and deployment of scalable AI, Machine Learning, and Generative AI solutions that improve product quality, operational excellence, and patient outcomes.
What you'll do
- Collect, clean, transform, and analyze large-scale structured and unstructured datasets related to product quality, patient complaints, manufacturing, and business operations.
- Develop predictive, prescriptive, and statistical analytics solutions to identify trends, risks, anomalies, and root causes.
- Design, build, and deploy production-grade AI/ML and Generative AI solutions using Large Language Models (LLMs).
- Develop enterprise AI applications such as Retrieval-Augmented Generation (RAG) systems, semantic search, AI copilots, intelligent assistants, and workflow automation solutions.
- Build scalable and reliable AI systems using modern MLOps/LLMOps, CI/CD, model monitoring, and deployment practices.
- Collaborate with software engineers, data engineers, architects, and business teams to operationalize AI solutions in enterprise environments.
- Implement responsible AI practices including model evaluation, governance, explainability, guardrails, and compliance alignment.
- Perform exploratory data analysis, feature engineering, statistical modeling, forecasting, clustering, classification, and time-series analysis.
- Prepare dashboards, reports, visualizations, and executive presentations to communicate insights and business impact.
- Work closely with quality, regulatory, manufacturing, and product complaint teams to support data-driven decision-making and continuous improvement.
- Stay current with emerging AI, GenAI, cloud, and analytics technologies and identify opportunities to accelerate enterprise AI adoption.
- Mentor junior team members and contribute to enterprise AI capability building and best practices.
What you'll need
- Master's or Bachelor's degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Biomedical Engineering, or a related quantitative field.
- 8–12 years of experience in advanced analytics, machine learning, AI solution development, or data science.
- Strong hands-on programming skills in Python and SQL.
- Proven experience building and deploying scalable AI/ML solutions in production environments.
- Strong understanding of statistical modeling, machine learning algorithms, predictive analytics, and data engineering concepts.
- Experience working with cross-functional teams in enterprise environments.
- Strong communication and stakeholder management skills with the ability to explain technical concepts to non-technical audiences.
- Ability to translate business problems into scalable and measurable AI solutions.
Nice to have
- Experience working in regulated industries such as biotech, pharmaceutical, healthcare, or manufacturing environments.
- Hands-on experience with Generative AI, Large Language Models (LLMs), and enterprise AI application development.
- Experience building Retrieval-Augmented Generation (RAG) systems, semantic search platforms, vector database solutions, and AI copilots.
- Familiarity with AI frameworks and ecosystems such as LangChain, LlamaIndex, Semantic Kernel, Hugging Face, OpenAI APIs, or similar technologies.
- Experience with MLOps/LLMOps practices including model deployment, monitoring, governance, CI/CD, and version control.
- Experience with cloud platforms such as AWS, Azure, or GCP and AI/ML platforms such as Databricks.
- Experience developing APIs, scalable pipelines, microservices, and enterprise AI integrations.
- Understanding of responsible AI, AI governance, model evaluation, hallucination mitigation, and compliance considerations.
- Experience with analytics and visualization tools such as Tableau, Power BI, Spotfire, S2, or similar platforms.
- Certifications in Python, SQL, Databricks, Cloud, AI/ML, or Generative AI technologies.
- Passion for innovation, continuous learning, and leveraging AI technologies to improve patient and business outcomes.
Details
- Location: Hyderabad, India.
Read the full description and apply on the company’s own careers page.