Senior Principal AI/ML Engineer
AbbottAbout the role
JOB DESCRIPTION:
Our medical devices 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 fingersticks.
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.
THE OPPORTUNITY
This Senior Principal AI/ML Engineer position can work out of our Santa Clara, CA location.
The Principal ML Ops Engineer will work from our Santa Clara 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 AI technology development with scalable engineering solutions. You will be vital in designing, developing and maintaining a robust AI platform, establishing production-grade MLOps capabilities, and collaborating closely with data scientists, infrastructure specialists, and algorithm teams to ensure effective AI solution deployments.
What You’ll Work On
Lead end-to-end ML solutions development and delivery, including data ingestion, annotation, feature engineering, training, validation, deployment, and monitoring.
Architect a highly available, secure, scalable cloud/on-prem hybrid ML infrastructure.
Engage directly with ML scientists and act as the team’s bridge/glue between science and engineering.
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.
Drive alignment and adoption of architecture strategy with business leaders.
Mentor and guide ML engineers and SW engineers, establish coding standards, and conduct detailed design and architectural reviews.
Qualifications
Bachelors Degree (± 16 years) in Computer Science, Engineering Mathematics, or related field.
Minimum 10+ years of experience, Master’s Degree with 7+ years of related experience, or Ph.D. with 5+ years of related experience.
Deep experience building ML infrastructure for experiment tracking, model training, data versioning, annotation tools, model serving, monitoring and observability.
Experience with GenAI and Agentic AI development infrastructure including grounding, RAG, MCP and prompt engineering.
Experience developing AI products on cloud computing platforms (e.g., AWS, Azure, Google Cloud), containerization technologies (e.g., Docker, Kubernetes), pipeline orchestration tools (e.g. Airflow), IaC (e,g., Terraform).
Proficient in tools like Azure ML SDK, Azure Data Factory, Databricks, Spark, or related technologies.
Strong understanding of database technologies (e.g., SQL, NoSQL) and data modeling principles.
Significant experience working with agile software development methods, such as scr
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