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 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 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 around the world 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 a best place to work for 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 system, innovative therapies for treating heart disease, or products that help people with chronic pain or movement disorders, our medical device technologies are designed to help people live their lives better and healthier. Every day, our technologies help more than 10,000 people have healthier hearts, improve quality of life for thousands of people living with chronic pain and movement disorders, and liberate more than 500,000 people with diabetes from routine finger sticks.

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 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.

• Lead end‑to‑end ML solutions 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 act as the team’s bridge/glue 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 guide ML engineers and data scientists, establish coding standards, and conduct detailed design and architectural reviews.

• 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 in building and deploying Machine Learning solutions using various ML algorithms and hands‑on experience with Python programming.
• Experience in building IT use cases / solutions especially around AI/ML cognitive services and platforms, Model productionization, and CICD Automation.
• Excellent understanding of Machine Learning techniques and proficiency in feature analysis, algorithm selection and model hyperparameter tuning.
• Experience of senior executive/leadership engagement.
• Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure and governance.
• Experience with NLP/NLG, AI…