Staff AI/Machine Learning Engineer

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 114,000 colleagues serve people in more than 160 countries.

     

JOB DESCRIPTION:

Staff AI/Machine Learning Engineer

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 115,000 colleagues serve people in more than 160 countries.

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to:

• Career development with an international company where you can grow the career you dream of.
• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution
• Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.
• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
• A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

The Opportunity

This position works out of our Plymouth, MN location in the Structural Heart Division. Our business purpose is to restore health and improve quality of life by designing and providing device and management solutions for treating structural heart disease.

The Staff AI/Machine Learning Engineer will provide technical leadership within a vibrant, high-performing R&D team that is redefining the treatment of structural heart disease. The incumbent will work cross-functionally across software engineering, clinical engineering and systems engineering to develop novel implementations of ML-enabled product features as part of a unique product ecosystem.

REQUIRED QUALIFICATIONS

• Bachelor’s degree in Biomedical Engineering, Computer Science, Data Science, Engineering, or similar with an emphasis in artificial intelligence and machine learning. Strongly prefer Master’s or PhD
• Minimum industry experience: 8 years with Bachelor’s, 6 years with Masters, 3 years with PhD
• Proficiency in common AI/ML programming languages (at least one of): Python (preferred), R, MATLAB, etc.
• Structured and unstructured database creation/usage to retrieve, store and query multimodal datasets
• Manipulation of large datasets, including pruning, wrangling, cleaning, normalizing, scaling, transforming, encoding, mitigating imbalance, etc.
• Experience with Exploratory Data Analysis (EDA) and feature engineering
• Training, evaluation and hyperparameter tuning of various types of machine learning algorithms
• Experience with tree-based, SVN, kNN and linear models
• Experience in building end-to-end pipelines within common modeling environments
• Solid knowledge of conventional statistics methods and tools.
• Self-motivated with ability to collaborate across multiple disciplines (e.g., clinical, software, systems) to meet program milestones.
• Excellent written and verbal skills and ability to speak to wide variety of stakeholders

PREFERRED QUALIFICATIONS

• Experience with multimodal data integration and ensemble model architectures
• Experience with common model serving runtimes, deployment tools and platforms
• Experience with LLM fine-tuning and architectures, such as encoder-decoder transformer models, including MoE, RAG and recurrent hybrids
• MLOps experience within Azure or AWS
• Experience with source control repositories such as Github
• Working knowledge of global data privacy regulations
• Experience in creating analytics reports and interactive visualizations
• Familiarity with ISO 13485, 14971, etc.
• Experience in compiling and optimization techniques (e.g., quantization, pruning, compression) to deploy models on edge devices
• Experienced in the sequential phases of the medical device development from early feasibility through development, test, commercial launch, and post-market support
• Experience in first-in-human and pivotal clinical trials
• Familiarity with cardiac anatomy and interventional cardiology

Apply Now

Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives:  www.abbottbenefits.com

Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.

Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott, and on Twitter @AbbottNews.

     

The base pay for this position is

$97,300.00 – $194,700.00

In specific locations, the pay range may vary from the range posted.

     

JOB FAMILY:

Product Development

     

DIVISION:

SH Structural Heart

        

LOCATION:

United States > Minnesota > Plymouth : 5050 Nathan Lane N

     

ADDITIONAL LOCATIONS:

     

WORK SHIFT:

Standard

     

TRAVEL:

Yes, 5 % of the Time

     

MEDICAL SURVEILLANCE:

Not Applicable

     

SIGNIFICANT WORK ACTIVITIES:

Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day), Keyboard use (greater or equal to 50% of the workday)

     

Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.

     

EEO is the Law link - English: http://webstorage.abbott.com/common/External/EEO_English.pdf

     

EEO is the Law link - Espanol: http://webstorage.abbott.com/common/External/EEO_Spanish.pdf