Senior Staff AI/ML 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. Descritivo de Cargo 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.

Abbott is an Equal Opportunity Employer, committed to employee diversity.

THE OPPORTUNITY

This Senior Staff AI/ML Engineer position can work out of our Santa Clara, CA location.

Senior Staff AI/ML Engineer will provide technical leadership for Abbott's Medical Devices Digital (MDD) AI initiatives, driving the architecture, scalability, and operational excellence of enterprise AI platforms.

This role bridges advanced AI innovation with production-grade engineering, defining technical strategy, establishing best practices for MLOps and AI governance, and leading the design and evolution of robust, scalable AI infrastructure.

The Senior Staff AI/ML Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment of AI solutions, ensure reliability and compliance, and influence the long‑term AI technology roadmap across the organization.

What You’ll Work On

• Work on 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 in Computer Science, Engineering Mathematics, or related field.
• Minimum 8+ years of experience, Master’s Degree with 6+ years of related experience, or Ph.D. with 4+ 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 scrum and Kanban and working within CI/CD pipelines.
• Experience incorporating Security by Design principles into AI product development.
• Experience of senior executive/leadership engagement.
• Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure and governance.
• Experience with microservices architecture and distributed systems.
• Experience in reviewing and selecting Technical and Applications Architectures solutions.
• Certifications and specializations in AI/ML, LLMs and Cloud platforms.
• Excellent oral, written and presentation communication skills.
• Team leadership experience and demonstrated mentorship capabilities.

Preferred

• Experience working in an FDA-regulated business (e.g. validated software related to medical, pharmaceutical, or life sciences products).
• Experience with FDA 510(k) submissions and clinical-grade ML product development.
• Solid understanding of the design thinking process, as well as a passion and know‑how for influencing design strategy.
• Publications, patents, or notable contributions to open‑source projects.
• Background in signal processing, computer vision, or multimodal learning.
• Familiarity with data security best practices, data anonymization, synthetic data generation, 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.

Família de Cargo Product Development Divisão MD Medical Devices Localidade United States > Santa Clara : Building B - SC Localidades Adicionais Turno de Trabalho Standard Viagem Yes, 5 % of the Time Vigilância médica Not Applicable Atividades de trabalho significativas

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)