Sr. AI/ML Engineer- Life Sciences

Job ID: 35000015Company: Abbott LaboratoriesLocation: United States - California - San DiegoJob Type: Full timeCategory: Research & DevelopmentIndustry: HealthcarePosted Date: 2026-07-31Abbott 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.Position OverviewThe Sr. Machine Learning Engineer, with minimal guidance from more experienced engineers, works independently and in collaboration with others on multiple projects which are complex in scope. This role applies deep knowledge of advanced artificial intelligence and machine learning algorithms and models to solve problems involving biological, genomic, clinical and healthcare data within a setting of advanced cancer screening and precision oncology. This role is involved at every step of the solution development process, from ideation, design, implementation and deployment. This role strongly contributes to the strategic vision for the application of cutting-edge AI methodologies at Exact Sciences and work as a partner with biostatisticians, bioinformatics scientists, and data scientists to further our goal of helping eradicate cancer by preventing it, detecting it earlier, and guiding personalized treatment.Essential DutiesInclude, but are not limited to, the following:Maintain deep expertise in one or more AI technology areas. Clearly present and communicate relevance of technological advances as relevant to our work in biostatistics, bioinformatics and data science at Exact Sciences.Develop perspectives on “AI technology affordance”: what do these advances in AI technology allow us to do (more efficiently and / or more effectively) that we couldn’t do before.Work with stakeholders to discover and refine requirements for ML- and AI-based solutions to business problems with a focus on bioinformatics, biostatistics and data engineering applications.Collaborate with other ML/AI engineers and relevant partners to design software solutions that utilize state-of-the art artificial intelligence and machine learning techniques.Work with other AI and ML engineers and software engineers to implement and deploy ML and AI solutions.Work in an Agile framework focused on iterative, rapid delivery of proof-of-concept solutions.Contribute to the development of an AI strategy at Exact Sciences that empowers the team to leverage both existing AI and ML tools and those developed in-house to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes.Contribute to internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices for leveraging them.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.Exercise discretion and judgment within broadly defined practices and policies in selecting methods and techniques and evaluation criteria for obtaining and interpreting results. Ability to apply strong communication skills and to explain difficult, sensitive, and/or complex information to audiences of peers.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.Ability to act with an inclusion mindset and model these behaviors for the organization.Ability to work designated schedule.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 QualificationsPh.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 without sponsorship.Preferred Qualifications2+ years of life sciences industry experience working with biological data.2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.Basic knowledge of ML-Ops and processes for managing the versioning and deployment of machine learning models.Scientific understanding of cancer biologyThe base pay for this position is $78,000.00 – $156,000.00. In specific locations, the pay range may vary from the range posted.Skillsartificial intelligencemachine learningpythondeep learningreinforcement learningnatural language processingimage processingcomputer visionartificial neural networkstensorflowpytorchsklearnlarge language modelstransformer architectureretrieval augmented generationbioinformaticsbiostatisticsdata engineeringagilementorshipstakeholder managementscientific communicationversion controlmachine learning model deploymentdata miningcancer biologyml-ops