Job description

Primary Function of Position In this role, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary to support the entire machine learning lifecycle, from development to deployment. You will work closely with ML engineers and software developers across Intuitive to ensure that machine learning models are seamlessly integrated into our systems and deliver value at scale. The ideal candidate is an independent and fast-paced engineer with excellent problem-solving skills and practical working knowledge of modern ML development techniques. Essential Job Duties • Bootstrap and maintain a production-grade Kubernetes cluster, including CNI networking and storage integration • Deploy and configure ML orchestration tooling (e.g., Metaflow) and artifact/dataset storage solutions to support reproducible ML workflows • Validate GPU node health and configuration across heterogeneous hardware (B200, L40S, A6000, V100), including driver/CUDA standardization and topology checks • Design and execute team migration playbooks, working directly with engineering teams to port workflows, migrate datasets/artifacts, and roll out tool updates • Write and maintain runbooks, architecture documentation, and disaster recovery procedures • Participate in on-call rotation and incident response for platform-level issues • Collaborate with IT/Security on identity integration, access control, and compliance requirements • Continuously evaluate and adopt infrastructure best practices for reliability, cost, and developer experience Required Skills and Experience • 3+ years of experience in infrastructure, DevOps, or MLOps roles, or equivalent practical experience • Demonstrated experience operating Kubernetes in production (networking, storage, RBAC, troubleshooting) • Strong scripting/automation skills in Python and/or Bash; comfort with Infrastructure-as-Code tools (Ansible, Helm, Terraform, or similar) • Hands-on experience with at least one distributed storage system (S3, MinIO, NetApp, or similar) • Experience building or maintaining CI/CD pipelines (GitLab CI, ArgoCD, or equivalent) • Solid understanding of Linux systems administration and networking fundamentals • Excellent communication and documentation skills, with the ability to write clear runbooks and migration guides • High degree of autonomy and comfort working across the full stack, iteratively building solutions Required Education and Training • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field; or equivalent experience Preferred Skills and Experience • Experience with ML orchestration frameworks (Metaflow, MLflow, Kubeflow, or similar) • Familiarity with GPU infrastructure (NVIDIA drivers, CUDA, NVLink/NUMA topology, MIG partitioning) • Prior experience in a regulated industry (healthcare, finance, or similar) where auditability and access control are critical • Experience leading or supporting large-scale infrastructure migrations with multiple stakeholder teams Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role. Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws. Mandatory Notices U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status. Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process). For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws. Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee. This position may be filled at a different job level than listed here depending on business need and/or on the selected candidate’s experience, knowledge and skills. Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law. We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.

Requirements

Must-haves

Primary Function of Position
Essential Job Duties
Bootstrap and maintain a production-grade Kubernetes cluster, including CNI networking and storage integration
Deploy and configure ML orchestration tooling (e.g., Metaflow) and artifact/dataset storage solutions to support reproducible ML workflows
Validate GPU node health and configuration across heterogeneous hardware (B200, L40S, A6000, V100), including driver/CUDA standardization and topology checks
Design and execute team migration playbooks, working directly with engineering teams to port workflows, migrate datasets/artifacts, and roll out tool updates
Write and maintain runbooks, architecture documentation, and disaster recovery procedures
Participate in on-call rotation and incident response for platform-level issues
Collaborate with IT/Security on identity integration, access control, and compliance requirements
Continuously evaluate and adopt infrastructure best practices for reliability, cost, and developer experience
Required Skills and Experience
3+ years of experience in infrastructure, DevOps, or MLOps roles, or equivalent practical experience
Demonstrated experience operating Kubernetes in production (networking, storage, RBAC, troubleshooting)
Strong scripting/automation skills in Python and/or Bash; comfort with Infrastructure-as-Code tools (Ansible, Helm, Terraform, or similar)
Hands-on experience with at least one distributed storage system (S3, MinIO, NetApp, or similar)
Experience building or maintaining CI/CD pipelines (GitLab CI, ArgoCD, or equivalent)
Solid understanding of Linux systems administration and networking fundamentals
Excellent communication and documentation skills, with the ability to write clear runbooks and migration guides
High degree of autonomy and comfort working across the full stack, iteratively building solutions
Required Education and Training
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field; or equivalent experience
Experience with ML orchestration frameworks (Metaflow, MLflow, Kubeflow, or similar)
Familiarity with GPU infrastructure (NVIDIA drivers, CUDA, NVLink/NUMA topology, MIG partitioning)

Nice-to-haves

Preferred Skills and Experience

Application prep

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Keywords to mirror

machine learningmlkubernetespythonci/cd

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