Job Description Summary

GE Vernova is seeking a technical and people leader to build, scale, and lead a global DevOps and MLOps capability that enables advanced industrial R&D, digital engineering, and AI driven innovation across the energy value chain.

This role will design and operate secure, reliable, and scalable DevOps and MLOps platforms that support agile development of software, controls, digital twins, analytics, and machine learning solutions used in mission critical, regulated energy environments. The successful candidate will partner and collaborate closely with engineering, data science, and product teams to accelerate innovation while meeting the highest standards of quality, safety, cybersecurity and compliance.

Job Description

Major Responsibilities:

DevOps & MLOps Strategy

Define and execute the global DevOps / MLOps strategy aligned with GE Vernova’s R&D and Engineering objectives
Architect and govern industrial‑grade platforms supporting:
- Software and controls development
- AI/ML model lifecycle management
- Simulation, digital twins, and advanced analytics
Balance speed of innovation with engineering rigor, traceability, and regulatory requirements

Platform & Architecture Leadership

Design and oversee platforms for:
- CI/CD and CI/CT pipelines (including testing for industrial software and embedded systems where applicable)
- On-Prem, cloud, hybrid, and edge computing environments
- Secure ML training, deployment, monitoring, and retraining pipelines
- Drive adoption of infrastructure as code, automation, observability, and platform engineering best practices
- Evaluate, select, and integrate new tools and technologies that improve developer and data scientist productivity

MLOps for Industrial AI

Enable scalable, governed MLOps capabilities supporting:
- Predictive maintenance
- Asset performance optimization
- Grid analytics and energy transition solutions
Partner with data science and domain engineering teams to:
- Standardize ML workflows and model governance
- Ensure model explainability, traceability, and lifecycle management
- Support deployment in both cloud and edge environments

People & Organizational Leadership
- Build, lead, and develop a globally distributed inclusive and diverse DevOps and MLOps engineering team
- Establish clear technical roles, career paths, and employee-led development plans
- Foster a culture of engineering excellence, continuous improvement, safety, and accountability
- Lead global hiring, onboarding, performance management and talent development

Security, Compliance & Quality

Ensure platforms comply with:
- Cybersecurity standards
- Data governance and privacy requirements
- Industry and regulatory expectations relevant to energy and industrial systems
Embed security, quality, and reliability into all DevOps and MLOps pipelines (“secure by design”)

Stakeholder Partnership & Influence

Act as a strategic partner to:
- R&D and Engineering leadership
- R&D and AI teams, Cybersecurity, IT, and Enterprise Architecture
Translate complex engineering and business requirements into robust, scalable platform solutions
Communicate technical strategy and trade-offs effectively to senior leadership

Experience

Basic Qualifications:

Advanced degree in Engineering, Computer Science, or related field
10+ years of experience in DevOps, platform engineering, or cloud infrastructure
5+ years leading global, multidisciplinary engineering teams
Proven experience supporting industrial, product, or R&D engineering organizations
Hands-on experience implementing MLOps in production, preferably for industrial AI use cases

Technical Expertise

Strong experience with:
- CI/CD tools and automation, including test automation
- Cloud platforms (AWS, Azure, GCP) and hybrid architectures
- Containers and orchestration (Docker, Kubernetes)
- Infrastructure as Code (Terraform, ARM, CloudFormation, etc.)
- Ability to audit teams adopting DevOps / MLOps for compliance against a maturity framework
Practical knowledge of MLOps frameworks and platforms (e.g., MLflow, Kubeflow, Azure ML, SageMaker)
Understanding of industrial cybersecurity, reliability, and compliance constraints
Agile development teams and awareness of NPI processes and Scaled Agile Framework

Leadership & Collaboration

Proven ability to lead and scale high‑performing global teams
Strong coaching, mentoring, and talent development skills
Excellent communication skills across technical and non‑technical audiences
Ability to influence without authority in a complex matrix organization

Desired

Experience in energy, power systems, renewables, grid, or heavy industrial domains
Exposure to embedded software, controls, or edge AI deployments
Experience with digital twins, simulation platforms, or physics‑based models

Whats Success Looks Like

R&D and engineering teams can rapidly develop, test, deploy, and operate industrial software and AI solutions
TTM and Quality are improved by adoption of DevOps / MLOps systems, measured by KPI for continuous improvement
DevOps and MLOps platforms are secure, standardized, and trusted across the organization
AI and digital innovation move faster while maintaining engineering quality and regulatory compliance
Teams are engaged, growing, and recognized as strategic enablers of GE Vernova’s energy transition mission

Additional Information

Relocation Assistance Provided: No

GE Vernova

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