Senior AI/ML Engineer – Life Sciences

Stellenbeschreibung:

Guide the architecture, technical roadmap, and strategic evolution of Abbott’s life sciences generative AI platform
Design and implement shared platform services, reusable components, and supported solution patterns
Integrate agent frameworks and interoperability protocols with enterprise data sources, document repositories, and scientific systems
Partner with stakeholders and AI/ML engineers across science and medical functions to translate workflows, SOPs, and business needs into scalable AI solutions
Define and apply evaluation criteria for solution quality, reliability, efficiency, and business value
Apply Agile practices to develop, evaluate, and mature concepts into validated, reusable solutions
Provide mentorship and coaching to junior team members
Act as a subject matter expert in core and cross-functional meetings
Communicate complex information to technical and non-technical stakeholders
Support and comply with Abbott’s Quality Management System policies and procedures
Maintain regular and reliable attendance and availability during the designated work schedule
Model inclusion, accountability, innovation, integrity, quality, and teamwork

Requirements

Ph.D. in Statistics, Computational Biology, Computer Science, or related quantitative field, or master’s degree in one of these fields 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
3+ years of experience with artificial intelligence and machine learning algorithms
Knowledge and experience with artificial neural networks, deep learning, and reinforcement learning
Knowledge and experience with AI/ML techniques in natural language processing, image processing and computer vision, or image and pattern recognition
Knowledge and experience with large language models, transformer architecture, and retrieval augmented generation
Strong programming ability with demonstrated experience in Python and TensorFlow, PyTorch, or SKLearn
Knowledge and experience working with open-source AI models
Ability to perform essential duties with or without accommodation
Authorization to work in the United States without sponsorship
Preferred: 2+ years of life sciences industry experience working with biological data
Preferred: 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics
Preferred: Expertise in healthcare data mining
Preferred: Basic knowledge of ML-Ops and machine learning model versioning and deployment
Preferred: Scientific understanding of cancer biology
Ability to work on a mobile device, tablet, or computer screen and/or perform typing for approximately 85% of a typical working day
Ability to travel 5% of working time away from the work location

Core Competencies

Demonstrates expertise in artificial intelligence and machine learning, particularly in the context of life sciences, with strong programming skills in Python and experience with frameworks like TensorFlow and PyTorch. Capable of guiding technical roadmaps and collaborating with cross-functional teams to develop scalable AI solutions.