Senior Staff ML Ops Engineer

Abbott (abbottcareers2 board); Santa Clara (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

HIPAA/GDPR compliance program

Tuition reimbursement

Excellent retirement plan

Job summary

Abbott is seeking a Senior Staff ML Ops Engineer to lead the architecture and operational excellence of enterprise AI platforms in Santa Clara, CA. You will partner with data scientists, infrastructure teams, and product leaders to accelerate AI deployment while ensuring reliability and compliance.

Responsibilities include building scalable ML infrastructure, implementing robust CI/CD, and guiding a team of ML and software engineers through design and governance reviews.

Qualifications

• This role requires 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 with cloud platforms (AWS/Azure/GCP) and containerization/orchestration, CI/CD pipelines.
• Strong knowledge of regulatory/privacy standards (HIPAA, GDPR) and SaMD guidelines.

Responsibilities

• Architect a highly available, secure, scalable ML infrastructure across cloud and on-prem environments.
• Lead CI/CD workflows for ML models including testing, rollout, rollback, and governance.
• Mentor ML and SW engineers; establish coding standards and conduct design reviews.
• Collaborate with data scientists, infrastructure teams, and business leaders to align AI strategy.

Skills

ML Ops

Cloud architecture

Git & CI/CD

Regulatory compliance

Data governance

Python

SQL

Agile/Scrum

Security by design

Education

Bachelor's Degree in CS/Engineering/Math

Master's or PhD with related experience

Tools

Azure ML SDK

Azure Data Factory

Databricks

Spark

Terraform

Docker

Kubernetes

Airflow

Job description

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 122,000 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 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 Staff ML Ops Engineer position can work out of our Santa Clara, CA location.

Senior Staff ML Ops 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 ML Ops 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

• Architect a highly available, secure, scalable cloud/on-prem hybrid ML infrastructure that includes data ingestion, annotation, feature engineering, training, validation, deployment, and monitoring.
• 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.

  Preferred

  • Experience workin