Senior AI Platform Engineer, Life Sciences

Abbott

United States

Remote

USD 78,000 - 156,000

Full time

14 days+

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Job summary

Abbott is seeking a Sr. AI/ML Engineer to guide architecture, roadmap, and hands-on implementation for a life sciences AI platform across clinical and research functions. This role focuses on generative AI, scalable services, and secure patterns within a healthcare setting.

You will collaborate with Bioinformatics, Biostatistics, and Data Science teams, translating SOPs into AI-enabled solutions while driving platform adoption and maintaining quality standards in a regulated environment.

Qualifications

Ph. Din Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties, or master’s degree in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties plus 4 years of experience in lieu of a Ph.D.
3+ years of experience in statistics, computational biology, applied mathematics, or related quantitative field as outlined in the essential duties.
3+ years of experience with artificial intelligence and machine learning algorithms.
Demonstrated knowledge and experience with advanced AI concepts, such as artificial neural networks, deep learning, and reinforcement learning.
Demonstrated knowledge and experience using artificial intelligence and machine learning techniques within one or more of the following fields: natural language processing, image processing and computer vision, image and pattern recognition.
Demonstrated knowledge and experience with large language models for generative AI and associated concepts, such as transformer architecture and retrieval augmented generation.
Strong programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow,PyTorch, orSKLearn.
Knowledge of and experience working with open-source AI models.
Demonstrated ability to perform the essential duties of the position with or without accommodation.
Authorization to work in the United States without sponsorship.

Responsibilities

Guide the architecture, technical roadmap, and strategic evolution of the life sciences generative AI platform, including its runtime, gateway, memory, identity, observability, and evaluation capabilities, to accelerate and improve scientific and medical processes and outcomes.
Design and implement shared platform services, reusable components, and supported solution patterns that generalize recurring needs and reduce reliance on function-specific point solutions.
Integrate agent frameworks and interoperability protocols with enterprise data sources, document repositories, and scientific systems using secure, supported platform patterns.
Partner with stakeholders and AI/ML engineers across science and medical functions to translate operational workflows, SOPs, and business needs into scalable, supported AI solutions.
Drive platform adoption by defining and applying evaluation criteria that demonstrate solution quality, reliability, efficiency, and business value.
Apply Agile practices to iteratively develop, evaluate, and mature promising concepts into validated, reusable solutions.
Provide mentorship and coaching to more junior level team members.
Act as resource and subject matter expert in core team and/or cross-functional meetings.
Communicate difficult, sensitive, and complex information clearly to technical and non-technical stakeholders.
Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
Support and comply with the company’s Quality Management System policies and procedures.