- Drive development of enterprise-levelGenAIapplications using LLM frameworks such asLangchain,Autogen, and Hugging Face.
- Architect intelligent pipelines usingPySpark, TensorFlow, andPyTorchwithin Databricks and AWS environments.
- Implement embedding models andmanageVectorStoresfor retrieval-augmented generation (RAG) solutions.
- Integrate andleverageMDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems.
- Utilize SQL and Python for data engineering, data wrangling, and pipeline automation.
- Build scalable APIs and services to serveGenAImodels in production.
- Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems.
- Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations.
Basic Qualifications and Experience:
- Master s degree with8-10years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR
- Bachelor s degree with 10 - 14 years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR
- Diploma with 14 - 16 years of hands-on experience in Data Science, AI/ML technologies, or related technical domain
Functional Skills:
Must-Have Skills:
- 10+ years of experience working in AI/ML or Data Science roles, includingdesigningand implementingGenAIsolutions.
- Extensive hands-on experience with LLM frameworks and tools such asLangchain,Autogen, Hugging Face, OpenAI APIs, and embedding models.
- Strong programming background with Python,PySpark, and experience in building scalable solutions using TensorFlow,PyTorch, and SK-Learn.
- Proventrack recordof building and deploying AI/ML applications in cloud environments such as AWS.
- Expertisein developing APIs, automation pipelines, and servingGenAImodels using frameworks like Django,FastAPI, andDataBricks.
- Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices.
- Guide the team on development activities and lead the solution discussions
- Must have core technical capabilities inGenAI, Data Science space
Good-to-Have Skills:
- Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows.
- Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations.
- Proficiencyin tools like JIRA and Confluence for Agile delivery and project collaboration.
- Familiarity with MongoDB,VectorStores, and modern architecture principles for scalableGenAIapplications.
Professional Certifications:
- Any ETL certification (e.g.Informatica)
- Any Data Analysis certification (SQL)
- Any cloud certification (AWS or AZURE)
- Data Science and ML Certification
Soft Skills:
- Strong analytical abilities to assess and improve master data processes and solutions.
- Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders.
- Effective problem-solving skills to address data-related issues and implement scalable solutions.
- Ability to work effectively with global, virtual teams
