Job Description Summary

We are seeking an HPC Performance & Reliability Engineer to join our software engineering team supporting the development of gas turbine design tools. This is a critical individual contributor role responsible for profiling, benchmarking, and optimizing the performance of a diverse portfolio of engineering applications running on a hybrid HPC environment, with a majority of compute in AWS.
The successful candidate will establish best practices for job configuration, lead scaling studies, coordinate SLURM job launch configurations, and proactively monitor HPC resource usage to ensure a reliable and efficient compute environment for our internal engineering users.
This role works in close partnership with the IT team and serves as the technical focal point for HPC performance, coordinating efforts across bubble assignment contributors and maintaining the documentation and standards that guide our user community.

Job Description

Key Responsibilities

Application Profiling & Performance Analysis

• Evaluate, select, and deploy profiling tools appropriate for a mixed application environment including Fortran/C++/Python applications using OpenMP and MPI parallelism, as well as third-party commercial solvers (ANSYS and Siemens FEA/CFD products)
• Conduct systematic profiling of engineering applications to identify performance bottlenecks, inefficient resource utilization, and optimization opportunities
• Perform scaling studies across varying job sizes and processor counts to characterize how different application types and problem sizes perform as compute resources scale
• Develop and maintain a library of performance benchmarks and profiling results for key applications in the portfolio
• Translate profiling findings into actionable recommendations for job configuration and resource allocation

SLURM Configuration & Job Launch Optimization

• Own and maintain SLURM job launch scripts and configurations, working directly with the IT team to implement and validate changes
• Determine and document optimal job settings including CPU/memory allocation, AWS instance type selection, MPI/OpenMP thread configurations, and SLURM scheduler parameters for different application types and job sizes
• Coordinate with IT to ensure SLURM configurations reflect current HPC infrastructure capabilities and AWS environment changes
• Serve as the technical focal point for bubble assignment contributors working through the profiling backlog, establishing standards and reviewing their outputs

User Engagement & Job Characterization

• Proactively engage with new and existing user groups to understand their workflows, application usage patterns, and compute requirements
• Analyze job logs and scheduler data to identify new workload types, unusual resource consumption patterns, or uncharacterized applications that require profiling
• Work with users and team leads to prioritize profiling and optimization efforts based on business impact and resource consumption
• Maintain a current understanding of the full portfolio of job types submitted to the HPC environment

User Education & Documentation

• Communicate profiling results and scaling study findings directly to engineering users in a clear and actionable format
• Develop and maintain documentation of recommended job configurations, core count selection guidance, and best practices tailored to specific application types and job sizes
• Educate users on how to select appropriate compute resources based on job type, problem size, and performance tradeoffs
• Establish and maintain best practice standards for job submission across the user community

Monitoring & Proactive Reliability

• Define the data requirements and key metrics needed to support HPC monitoring dashboards, partnering with the dashboard development resource to ensure operational visibility
• Actively monitor HPC usage and resource metrics to detect anomalies including abnormal resource consumption by new or existing users, elevated job failure rates, increased queue times, unusually low utilization, and node availability issues
• Investigate anomalies proactively, resolving or escalating issues before they impact users
• Maintain proactive communication with users and stakeholders when issues are identified or changes are planned

Required Qualifications

• Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum 8 years of experience
• This role requires use of technical data subject to U.S. Government export restrictions and this posting is only for U.S. Persons (U.S. Citizens, lawful permanent residents and protected individuals (e.g., certain refugees and asylees)). GE will require proof of status prior to employment

Desired Skills & Qualifications

• Understanding of HPC architectures, job scheduling concepts, and parallel computing paradigms
• Hands-on experience with SLURM — configuration, job script development, scheduler tuning, and troubleshooting

• Ability to interpret profiling data and translate findings into concrete configuration and code-level recommendations
• Experience benchmarking and conducting scaling studies (strong/weak scaling analysis)

• Proficiency in Python and shell scripting for scripting, automation, and data analysis of job logs and performance metrics
• Working knowledge of Fortran and/or C++ sufficient to understand application structure and interpret profiling output — development expertise not required

• Familiarity with ANSYS and/or Siemens simulation products (FEA/CFD solvers such as ANSYS Mechanical, Fluent, or Siemens STAR-CCM+) and their HPC deployment and licensing models is strongly preferred

• Strong written and verbal communication skills with the ability to convey technical findings to both engineering users and IT stakeholders

This role requires access to U.S. export-controlled information. If applicable, final offers will be contingent on ability to obtain authorization for access to U.S. export-controlled information from the U.S. Government. ​

Additional Information

 

 

For candidates applying to a U.S. based position, the pay range for this position is between $127,700.00 and $212,700.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.

 

 

Bonus eligibility: discretionary annual bonus.

 

 

This posting is expected to remain open for at least seven days after it was posted on May 19, 2026.

 

 

Available benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.

 

 

GE Vernova Inc. or its affiliates (collectively or individually, “GE Vernova”) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.