AI/ML Engineer

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Job Overview:

Develop and implement fit for purpose AIML models, algorithms, foundation models to address pharma/healthcare applications. Transition innovative prototypes into production-grade solutions, including automation engines and client-ready deliverables. Evaluate model viability and scalability to ensure successful deployment. Rapidly translate research concepts into real-world applications at scale. Lead the design, testing, and delivery of solutions from post-prototype stages through to final client implementation.

Essential Functions:

• Assists with the ongoing development and implementation of an enterprise architecture, including presenting business cases and strategic release plans to senior leadership.
• Collaborates with product development to align IT strategy with business goals, ensuring long-term capability and process improvements within the enterprise framework.
• Engages in cross-functional teams, offering technical and system expertise, and may act as a consultant on system design and implementation.
• Stays up to date with emerging technologies, identifies opportunities for innovation, and leads or participates in R&D projects using standard project management practices.
• Provides guidance and mentorship to junior architects and business analysts, fostering growth and knowledge sharing within the team.

Key Technical Skills:

• Strong experience in Natural Language Processing, Machine Learning, and Deep Learning, including transforming natural language into features and applying the right algorithms and tools.
• Deep knowledge of Generative AI and Large Language Models, including fine-tuning, deployment strategies, and extending ML frameworks for NLP tasks.
• Proven ability to write scalable, maintainable code with experience in unit testing (e.g., Pytest) and understanding of Python’s multi-process architecture and threading limitations.
• Skilled in working with REST APIs and frameworks like Flask, FastAPI, and optionally Django or Pyramid.
• Familiarity with advanced NLP concepts such as Named Entity Recognition (NER) and Knowledge Graphs.

Educational Qualification: