Sr. AI/ML Engineer- Life Sciences

Abbott (abbottcareers2 board); United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Abbott is seeking a Sr. AI/ML Engineer to guide architecture and roadmap for a life sciences generative AI platform. You will work with Bioinformatics, Biostatistics and Data Science teams, translating complex workflows into scalable AI solutions while mentoring colleagues and aligning with Abbott's quality and inclusion standards. The role requires US work authorization and occasional travel.

Qualifications

• Ph.D. or Master’s in Statistics, Computational Biology, Computer Science, or related field per duties plus experience.
• 3+ years in statistics, computational biology, applied mathematics, or related field.
• 3+ years of experience with AI and ML algorithms.
• Strong knowledge of AI concepts: neural networks, deep learning, and reinforcement learning.
• Experience with NLP, image processing/vision, or related areas.
• Experience with large language models and transformer architecture.
• Proficiency in Python and ML frameworks (TensorFlow/PyTorch/SKLearn).
• Knowledge of open-source AI models is a plus.
• Authorization to work in the United States.

Responsibilities

• Guide architecture, roadmap, and evolution of the life sciences generative AI platform.
• Design shared platform services and reusable components to generalize needs.
• Integrate agent frameworks with enterprise data sources and systems.
• Collaborate with science and medical teams to translate workflows into AI solutions.
• Define evaluation criteria to demonstrate quality, reliability, and value.
• Apply Agile practices to mature concepts into usable solutions.
• Mentor junior team members and provide SME guidance.
• Represent SME in cross-functional meetings and communicate complex ideas clearly.
• Uphold Abbott’s mission, quality policies, and inclusion values.
• Travel up to 5% as required.

Skills

Python

TensorFlow

PyTorch

SKLearn

NLP

Computer Vision

Reinforcement Learning

Transformer architecture

Retrieval augmented generation

Open-source AI models

Education

PhD in Statistics/Computational Biology/CS or related field

Tools

TensorFlow

PyTorch

SKLearn

Job description

About Abbott

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries.

JOB DESCRIPTION:

Position Overview

The Sr. AI/ML Engineer guides the architecture, technical roadmap, and hands‑on implementation of the life sciences AI platform providing the foundations for agentic solutions across the science and medical offices. This role helps shape the organization's AI strategy and evaluates emerging state-of-the‑art technologies for practical implementation within the platform. This role serves both technical consumers in the Bioinformatics , Biostatistics and Data Science group, and non-technical consumers across Clinical Affairs, Regulatory Affairs, and Medical Operations within a setting of advanced cancer screening and precision oncology. The work combines pragmatic experimentation with a clear path beyond prototypes, producing solutions that are evaluated, validated, governed, supported, and reusable. This role defines the engineering standards, controls, and validation framework under which generative AI solutions are developed and published, and provides technical leadership through mentorship and architecture review.

Essential Duties

• 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 d efining 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.


• Maintain regular and reliable attendance and availability during the designated work schedule.


• Act with an inclusion mindset and model these behaviors for the organization.


• Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day.


• Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications

• Ph. D in 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 , or SKLearn .


• 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 wi