REQ-10050861
5月 09, 2025
Mexico

摘要

This position is pivotal in identifying and incubating cutting-edge AI technologies that align with
the strategic goals of the company, enhancing the capabilities in data-driven decision-making
and is crucial in defining and promoting best practices in AI model development and
deployment.
AI Engineer through their forward-thinking ensure seamless integration of innovative AI
solutions into existing frameworks, ensuring they are scalable, reliable, and tailored to meet the
unique demands of the pharmaceutical industry. The AI Engineer will con-tribute to our mission
of advancing healthcare through technology, ultimately improving patient outcomes and driving
business success

About the Role

Key Responsibilities:
• Understand complex and critical business problems, formulates integrated analytical 
approach to mine data sources, employ statistical methods and machine learning 
algorithms to contribute to solving unmet medical needs, discover actionable insights, 
and automate processes for reducing effort and time for repeated use.
• Architect and develop end-to-end AI/ML and Gen AI solutions, focusing on scalability, 
performance, and modularity while ensuring alignment and best practices with 
enterprise architecture standards.
• Manage the implementation and adherence to the overall data lifecycle of enterprise 
data from data acquisition or creation through enrichment, consumption, retention, and 
retirement, enabling the availability of useful, clean, and accurate data throughout its 
useful lifecycle.
• High agility to be able to work across various business domains. High agility to be able to 
work across various business domains. Integrate business presentations, smart 
visualization tools and contextual storytelling to translate findings back to business
users with a clear impact.
• Independently manage budget, ensuring appropriate staffing and coordinating projects 
within the area.
• Collaborate with globally dispersed internal stakeholders and cross-functional teams to 
solve critical business problems and deliver successfully on high visibility strategic 
initiatives.


Essential Requirements
• Advanced degree in Computer Science, Engineering, or a related field (PhD preferred).
Experience
• 5+ years of experience in AI/ML engineering (data engineering could be appropriate 
depending on experience), with at least 2 years focusing on designing and deploying 
LLM-based solutions.
• Strong proficiency in building AI/ML architectures and deploying models at scale with 
experience in cloud computing platforms such as AWS, Google Cloud, or Azure.
• Deep knowledge of LLMs and experience in applying them in business contexts.
• Knowledge of containerization technologies (Docker, Kubernetes) and CI/CD pipelines 
Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps tools for 
scalable deployment.
• Experience with API development, integration, and model deployment pipelines.
• Strong problem-solving skills and a proactive, hands-on approach to challenges.
• Ability to work effectively in cross-functional teams and communicate technical 
concepts clearly.
• Excellent organizational skills and attention to detail in managing complex systems.

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? http://www.novartis.com/about/strategy/people-and-culture

Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: http://talentnetwork.novartis.com/network

Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: http://www.novartis.com/careers/benefits-rewards

A female Novartis scientist wearing a white lab coat and glasses, smiles in front of laboratory equipment.
REQ-10050861

Data Science DD&IT US&I

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