Senior AI/ML Engineer – Life Sciences

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the architectural design, technical strategy, and progressive development of Abbott’s generative AI platform for life sciences.

• Develop and implement shared platform services, reusable components, and standardized solution patterns.

• Integrate agent frameworks and interoperability protocols with enterprise data sources, document repositories, and scientific systems.

• Collaborate with stakeholders and AI/ML engineers across scientific and medical domains to convert workflows, SOPs, and business requirements into scalable AI solutions.

• Establish and apply evaluation metrics for assessing solution quality, reliability, efficiency, and overall business impact.

• Utilize Agile methodologies to develop, assess, and refine concepts into validated, reusable solutions.

• Offer mentorship and guidance to junior team members.

• Serve as a subject matter expert during core and cross-functional meetings.

• Effectively communicate complex information to both technical and non-technical stakeholders.

• Adhere to and support Abbott’s Quality Management System policies and procedures.

• Ensure consistent and dependable attendance and availability as per the designated work schedule.

• Exemplify values of inclusion, accountability, innovation, integrity, quality, and teamwork.

⛳️ Requirements

• Ph.D. in Statistics, Computational Biology, Computer Science, or a related quantitative discipline, or a master’s degree in one of these areas with 4 years of relevant experience in lieu of a Ph.D.

• Over 3 years of experience in statistics, computational biology, applied mathematics, or a related quantitative field.

• More than 3 years of experience working with artificial intelligence and machine learning algorithms.

• Familiarity and experience with artificial neural networks, deep learning, and reinforcement learning techniques.

• Knowledge and hands-on experience with AI/ML techniques in natural language processing, image processing and computer vision, or image and pattern recognition.

• Proficiency and understanding of large language models, transformer architecture, and retrieval augmented generation.

• Strong programming skills, with proven experience in Python and frameworks such as TensorFlow, PyTorch, or SKLearn.

• Experience with open-source AI models.

• Capability to perform essential job functions with or without accommodation.

• Authorization to work in the United States without the need for sponsorship.

• Preferred: At least 2 years of experience in the life sciences industry, specifically working with biological data.

• Preferred: 2+ years of industry experience in molecular diagnostics, ideally in cancer diagnostics.

• Preferred: Expertise in healthcare data mining.

• Preferred: Basic understanding of ML-Ops and the versioning and deployment of machine learning models.

• Preferred: Scientific knowledge of cancer biology.

• Ability to work on a mobile device, tablet, or computer screen and/or type for approximately 85% of a typical workday.

• Willingness to travel up to 5% of working time away from the primary work location.

🏝️ Benefits

• Commitment to being an Equal Opportunity Employer for Minorities, Women, Individuals with Disabilities, and Protected Veterans.

• A travel requirement of 5% may involve overnight and weekend travel.