Software Configuration Management Engineer – Hardware
India, BengaluruPosted Aug 28, 2026
Overview
- Added in 30 days
- 658
- At this company, still open
Skills named in this posting
- Python
- Perl
For two decades, we have pioneered visual computing, the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning. This new model - where deep neural networks are trained to recognize patterns from massive amounts of data - has shown to be deeply effective at solving some of the most complex problems in everyday life. NVIDIA runs a very large GitLab environment, supporting 10s of thousands of engineers and massive repositories across the globe. Our Software Configuration Management (SCM) Tools and Infrastructure group is looking for a top SCM architect. You will tackle the challenges that we face with operating at scale to produce a best-in-industry solution and enable us to continue to provide unprecedented performance and reliability for our users. You will take on the challenges that come with operating and scaling our ever-growing GitLab deployment. In this role, you will design and code processes and automation tools to improve productivity managing and administering the SCM systems and applications used by our globally distributed engineering teams.
What You’ll Be Doing:
• Responsible for the full SCM environment including application, OS, and server hardware components, developing the continued automation and innovation needed for our large environment
• Create new solutions to improve the reliability and performance of our ever-growing infrastructure, and work with automated orchestration tools to deploy those improvements to hundreds of systems worldwide
• Be part of a global team and will evaluate technology alternatives, work closely with other project members to specify solutions, craft schedules, and lead ongoing enhancements and support
• Lead or contribute to GitLab upgrades and migrations, architectural reviews and design docs, root cause analysis and systemic fixes
• Learn and greatly improve the daily productivity of the world’s top chip designers and software engineers
What We Need to See:
• MS (preferred) or BS in Computer Science (or equivalent experience) or a related field with at least 3+ years of experience
• Deep understanding of SCM processes and large-scale, multi-site GitLab environments (experience with other SCM tools such as Perforce, Subversion, or ClearCase is a plus).
• You've configured/deployed Continuous Integration (CI) and Continuous Deployment (CD) systems in your past experience
• Excellent interpreted language skills highly desired – Object Oriented Perl or Python preferred and Strong software engineering process skills required
• Strong skills in scripting and object-oriented languages such as Python or Ruby, with solid software engineering practices and familiarity with design patterns.
• Hands-on experience with relational databases (PostgreSQL preferred)
• Experience with DevOps or system administration on Linux systems required (Rocky Linux 8, CentOS/RHEL, and Ubuntu preferred)
• Strong experience with automation required, Ansible or Puppet preferred and Excellent
• interpersonal skills, including written and verbal communication
• You are comfortable and enjoy working with dynamic and ever evolving environments
Ways to Stand Out from the Crowd:
• Meticulous and proactive problem-solver with a positive, can-do attitude.
• Demonstrate use of out-of-box thinking for creative solutions to highly sticky problems
#LI-Hybrid
Apply on the employer's site
Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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