Senior AI/ML Engineer – Life Sciences

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

📋 Description

• Oversee the architecture, technical roadmap, and strategic development of Abbott’s generative AI platform for life sciences.

• Create and execute shared platform services, reusable components, and established solution patterns.

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

• Collaborate with stakeholders and AI/ML engineers in science and medical functions to convert workflows, SOPs, and business requirements into scalable AI solutions.

• Establish and implement evaluation criteria for solution quality, reliability, efficiency, and business value.

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

• Offer mentorship and guidance to junior team members.

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

• Convey complex information effectively to both technical and non-technical stakeholders.

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

• Ensure consistent and reliable attendance and availability during the designated work schedule.

• Travel approximately 5% of working time, which may include overnight or weekend trips.

⛳️ Requirements

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

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

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

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

• Background in natural language processing, image processing and computer vision, or image and pattern recognition.

• Proficient in working with large language models for generative AI, transformer architecture, and retrieval-augmented generation.

• Strong programming skills in Python and familiarity with one or more machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.

• Knowledge and experience with open-source AI models.

• Authorization to work in the United States without sponsorship.

• Ability to perform essential duties with or without reasonable accommodation.

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

• Preferred: Over 2 years of experience in the life sciences industry dealing with biological data.

• Preferred: More than 2 years of industry experience in molecular diagnostics, preferably in cancer diagnostics.

• Preferred: Expertise in healthcare data mining.

• Preferred: Basic understanding of MLOps and machine learning model versioning and deployment.

• Preferred: Scientific knowledge of cancer biology.

🏝️ Benefits

• Remote work arrangement (available in the United States of America: Remote).

• Travel at 5% of working time.

• Equal opportunity employment.