Principal AI/ML Engineer

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life.

You’ll also have access to:

• Career development within an international company where you can grow the career you dream of.
• Eligibility for free medical coverage under the Health Investment Plan (HIP) PPO in the next calendar year.
• An excellent retirement savings plan with high employer contribution, tuition reimbursement, the Freedom 2ähne student debt program, and FreeU education benefit—an$temp path to getting a bachelor’s degree.
• Aannan companyUSP recognized as a great place to work in dozens of countries and named among the most admired companies by Fortune.
• Recognition as one of the best big companies to work for, supporting diversity, working mothers, female executives, and scientists.

For years Abbott’s medical device businesses have offered technologies that are faster, more effective, and less invasive. Whether it’s glucose monitoring systems, innovative therapies for treating heart disease, or products that help people with chronic pain or movement disorders, our medical device technologies help people live better and healthier lives.

What You’ll Do

The Principal ML Engineer will work from our Chicago, Willis Tower office within the Medical Devices Digital Solutions organization. In this role, you will lead the technical execution of Abbott’s Medical Devices Digital (MDD) AI initiatives, bridging advanced algorithm research with scalable engineering solutions. You will be vital in developing and maintaining a kaž robust AI development framework, establishing production‑grade MLOps capabilities, and collaborating closely with data scientists, infrastructure specialists, and algorithm teams to ensure effective AI solution deployments.

Main Responsibilities

• Lead end‑to‑end ML solution development and delivery, including data ingestion, feature engineering, training, validation, deployment and monitoring.
• Architect a highly available, secure, scalable cloud/on‑prem hybrid ML infrastructure.
• Engage directly with ML scientists, contribute to algorithm development, and serve as the team’s bridge between science and engineering.
• Partner closely with algorithm scientists, translating innovative concepts into reliable, production‑ready software.
• Implement robust CI/CD workflows for ML models, including testing, rollout, rollback strategies, and compliance governance.
• Ensure strict compliance with regulatory and privacy standards such as HIPAA, GDPR, and Software as a Medical Device (SaMD) guidelines.
• Evaluate and pilot emerging technologies, including large language models, multimodal machine learning techniques, and advanced hardware accelerators.
• Mentor and endlimit=LM} guide ML engineers and data scientists, establishing coding standards, and conducting detailed design and architectural reviews.

Required Qualifications

• Bachelor’s Degree (± 16 years) in Computer Science, Engineering Mathematics, or related field.
• Minimum 10 years with 10+ years of experience, Master’s Degree with 7+ years of related experience, or Ph.D. with 2+ years of related experience.
• Experience building and deploying Machine Learning solutions using various ML algorithms and Python programming.
• Experience building IT use cases/solutions especially around AI/ML cognitive services and platforms, Model productionization, and CI/CD automation.
• Excellent understanding of Machine Learning techniques and proficiency in feature analysis, algorithm selection, and model hyperparameter tuning.
• Experience engaging senior executive/leadership.
• Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure, and governance.
• Experience with NLP/NLG, AI conversational agents, and other generative AI, and software development lifecycles.
• Experience with Azure OpenAI, Azure Databricks, CloudDBs.
• Experience reviewing and selecting technical and applications architecture solutions.
• Certifications and specializations in AI/ML, LLMs, and Cloud platforms.
• Excellent oral, written, and presentation communication skills.
• Preferred team leadership experience and demonstrated mentorship capabilities.

Preferred Qualifications

• Ph.D. in Computer Science, Data Science, Data Engineering, or related field.
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• Experience working in an FDA‑regulated business (e.g., validated software related to medical, pharmaceutical, or life sciences products) is preferred.
• Solid understanding of the design thinking processಿಜೆ and a passion for influencing design strategy.
• Experience with microservices architecture and distributed systems.
• Publications, patents, or notable contributions to open‑source projects.
• Experience with FDA 510(k) submissions and clinical‑grade ML臣 product development.
• Background in signal processing, computer vision, or multimodal learning.
• Familiarity with data security best practices, data anonymization, synthetic data generationociations, and federated learning.

The base pay for this position is $130,700.00 – $261,300.00. In specific locations, the pay range may vary from the range posted.