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Specialized ML/LLM role with mid-level seniority at a recognizable pharma brand increases applicant competition moderately.
Core ML/LLM engineering skills are highly transferable across industries despite pharma context.
Explicit 6+ years and mandatory ML, MLOps, and LLM technology requirements increase shortlisting strictness.
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Develop and deliver AI-powered and machine learning solutions that accelerate medicine availability and business impact.
Build and maintain ML pipelines and integrate advanced AI models including generative AI and foundation models for scalable deployment.
Collaborate with business and IT stakeholders to operationalize AI solutions and educate teams on AI applications and value.
6+ years of experience with advanced data & analytics, including machine learning, Python/R programming, and cloud platforms (AWS, GCP, or Azure).
Proven skills in developing and deploying generative AI solutions and deep learning frameworks such as PyTorch or TensorFlow.
Experience with prompt engineering, vector databases, handling unstructured/semi-structured data, and MLOps/model development lifecycle.
Work Experience Required: 6+ years in data science or AI engineering roles.
Experienced in leading AI initiative implementations, especially with LLM-based and generative AI models.
Strong technical expertise in building AI pipelines, including frameworks like LlamaIndex, LangChain, and usage of Hugging Face models.
Able to communicate complex AI concepts and insights to both technical and non-technical stakeholders and drive AI adoption across business units.