Senior Staff MLOps Engineer

HCA Healthcare; Nashville (TN); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Comprehensive benefits

401(k) matching

Education support

Employee stock purchase plan

Job summary

The Senior Staff ML Ops Engineer at HCA Healthcare is a technical leader responsible for shaping our MLOps strategy, building a scalable, secure platform, and guiding cross-functional teams across data science, product, and engineering.

You will design cloud architectures, implement IaC with Terraform, develop ML pipelines, and promote responsible AI practices while mentoring engineers and driving reliability, observability, and governance across AI/ML workloads.

Qualifications

• Lead architecting enterprise MLOps platforms.
• 7+ years in software or DevOps roles.
• Strong collaboration with cross-functional teams.

Responsibilities

• Lead architecture and roadmap for AI/ML platform.
• Design and manage cloud infra with IaC.
• Collaborate with data science, product, and eng teams.
• Evaluate tools and vendors for MLOps.
• Improve reliability, observability, and fault tolerance.
• Build DevOps pipelines for ML workloads.
• Develop agent frameworks for autonomous monitoring.

Job description

Experience the HCA Healthcare difference where colleagues are trusted, valued members of our healthcare team. Grow your career with an organization committed to delivering respectful, compassionate care, and where the unique and intrinsic worth of each individual is recognized. Senior Staff MLOps Engineer

Job Summary and Qualifications

Position Summary

The Senior Staff ML Ops Engineer is a technical leader and key architect in shaping and driving our organization's MLOps strategy and practice. This role requires deep expertise in cloud architecture, machine learning operations, and DevOps principles, combined with a proven ability to lead technical initiatives, mentor engineers, and collaborate effectively with cross-functional teams.

The Senior Staff ML Ops Engineer will be responsible for designing, building, and maintaining a highly scalable, reliable, and secure MLOps platform that enables the efficient deployment and operation of AI/ML solutions across the organization. This role will champion best practices, drive innovation, and ensure the platform aligns with the company's strategic business objectives. This position is crucial for building a culture of Responsible AI.

Major Responsibilities

• Platform Architecture and Strategy: Lead the architectural design, development, and long-term roadmap for the organization's AI/ML platform. Define the vision, strategy, and technical standards, ensuring alignment with overall business and technology goals.
• Cloud Infrastructure Design and Management: Architect and manage the cloud infrastructure supporting the MLOps platform, leveraging infrastructure-as-code (IaC) tools like Terraform. Optimize for scalability, security, cost-effectiveness, and high availability.
• Cross-Functional Collaboration and Stakeholder Management: Partner with data science, product management, engineering, and business teams to understand their requirements and ensure the MLOps platform effectively supports their needs. Effectively communicate technical concepts and strategies to both technical and non-technical audiences.
• Vendor and Technology Evaluation: Evaluate and select appropriate tools, technologies, and vendors to support the MLOps platform. Stay abreast of emerging trends and advancements in the MLOps landscape.
• AI/ML Reliability and Observability: Collaborate with the AI/ML reliability engineering team to design and implement components that ensure the platform’s operational reliability, observability, and fault tolerance.
• DevOps for Machine Learning Workloads: Build and maintain robust DevOps pipelines tailored for ML workflows, enabling automated model training, testing, deployment, and monitoring.
• Agentic AI Platform Engineering: Build and operationalize intelligent agent frameworks that autonomously monitor, diagnose, and respond to system events, leveraging feedback-driven learning, observability, and orchestration to improve platform resilience and efficiency.

Education & Experience

• Bachelor's degree preferred
• Master's degree in Computer Science, Data Science, AI, or related field preferred
• 7+ years of experience in Software Engineering, Systems Engineer, Dev Ops, or related role required

Benefits

• Comprehensive benefits for medical, prescription drug, dental, vision, behavioral health and telemedicine services

• Wellbeing support, including free counseling and referral services

• Time away from work programs for paid time off, paid family leave, long- and short-term disability coverage and leaves of absence

• Savings and retirement resources , including a 401(k) Plan with a 100% match on 3% to 9% of pay (based on years of service), Employee Stock Purchase Plan, flexible spending accounts, preferred banking partnerships, retirement readiness tools, rollover support and financial wellbeing counseling

• Education support through tuition assistance, student loan assistance, certification support, dependent scholarships and a partnership with Galen College of Nursing

• Additional benefits for fertility and family building, adoption assistance, life insurance, supplemental health protection plans, auto and home insurance, legal counseling, identity theft protection and consumer discounts

Learn more about Employee Benefits (https://careers.hcahealthcare.com/pages/employee-benefits-and-rewards)

Note: Eligibility for benefits may vary by location.

HCA Healthcare has been recognized as one of the World's Most Ethical Companies® by the Ethisphere Institute more than ten times. In recent years, HCA Healthcare spent an estimated $3.7 billion in cost for the delivery of charitable care, uninsured discounts, and other uncompensated expenses.

"There is so much good to do in the world and so many different ways to do it."- Dr. Thomas Frist, Sr.

HCA Healthcare Co-Founder

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.