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Nsight Jobs in Texas (NOW HIRING)

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Nsight information

What are Nsight jobs?

Nsight jobs typically refer to positions at Nsight, a telecommunications company offering internet, phone, and IT services primarily in Wisconsin and Michigan. Employees at Nsight can work in various roles such as customer service, technical support, network engineering, sales, and IT. These jobs often involve helping customers with their services, maintaining network infrastructure, or developing new solutions. Nsight values teamwork, innovation, and customer satisfaction, and offers opportunities for professional growth in the tech and telecom industries.

What are the key skills and qualifications needed to thrive as a data analyst at Nsight?

To thrive as a Data Analyst at Nsight, you generally need strong analytical skills, proficiency in statistics, and a relevant degree in data science, mathematics, or a related field. Familiarity with data visualization tools (such as Tableau or Power BI), SQL databases, and possibly certifications like Microsoft Certified: Data Analyst Associate is typically expected. Attention to detail, effective communication, and problem-solving abilities help you interpret data and present actionable insights clearly to stakeholders. These skills enable accurate data-driven decision-making and facilitate collaboration across teams, driving organizational success.

What types of projects do employees typically work on at Nsight, and how do teams collaborate to achieve project goals?

At Nsight, employees often work on technology consulting projects that may include digital transformation, cloud migration, or IT infrastructure optimization. Teams are typically cross-functional, combining consultants, project managers, and technical specialists to tackle client challenges. Collaboration is highly valued, with regular meetings, clear communication channels, and shared project management tools to ensure everyone is aligned. Employees are encouraged to contribute ideas and work closely with clients, which helps build both technical and interpersonal skills.

What is the difference between Nsight vs Network Security Analyst?

AspectNsightNetwork Security Analyst
Required CertificationsTypically Cisco, CompTIA Security+CompTIA Security+, CISSP, CEH
Work EnvironmentIT consulting firms, tech companies, remote optionsCorporate IT departments, security firms, government agencies
Industry UsageTechnology, consulting, cybersecurityCybersecurity, IT, finance, government
Common Search/ComparisonYesYes

While Nsight professionals focus on providing IT consulting and solutions, Network Security Analysts specialize in protecting networks from threats. Both roles require cybersecurity certifications and work in tech environments, but Nsight roles often involve broader IT consulting, whereas Network Security Analysts focus specifically on security measures and threat mitigation.

What job categories do people searching Nsight jobs in Texas look for?

The top searched job categories for Nsight jobs in Texas are:

What cities in Texas are hiring for Nsight jobs?

Cities in Texas with the most Nsight job openings:

Infographic showing various Nsight job openings in Texas as of August 2026, with employment types broken down into 93% Full Time, and 7% Part Time. Highlights an 62% Physical, 5% Hybrid, and 33% Remote job distribution.

Senior Software Engineer, DGX Cloud AI Infrastructure

Nvidia

Austin, TX • On-site

$121K - $160K/yr

Full-time

Re-posted 29 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA is at the forefront of the generative AI revolution, building the software and systems that power the world's most advanced large language model workloads. We are looking for a Senior Software Engineer to lead the bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales we run. In this role you will set technical direction across communication libraries, model frameworks, and inference/training stacks to ensure state-of-the-art LLM workloads run efficiently and reliably at scale.

You will lead deep performance and reliability investigations on multi-GPU and multi-node deployments, define how we benchmark and qualify new platforms, and build the resilience and failure-attribution capabilities that keep large clusters productive. This is a hands-on senior individual-contributor role for an engineer who operates at the intersection of deep learning systems, GPU performance, distributed computing, and large-scale operations - and who raises the bar for the engineers around them. What you'll be doing: Lead bring-up, validation, and debugging of large-scale AI clusters, infrastructure, and end-to-end workloads, setting the standard for how the team operates.

Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks. Profile and optimize end-to-end workload performance across compute, memory, networking, and communication layers using tools such as Nsight Systems, NCCL tests, and custom microbenchmarks. Analyze scaling efficiency for distributed LLM workloads using data, tensor, pipeline, and expert parallelism across modern GPU clusters, and translate findings into concrete tuning guidance.

Own root-cause analysis of complex failures - hangs, performance regressions, topology sensitivity in large distributed environments. Define and build the resilience and failure-attribution stack: detecting, triaging, and attributing node, fabric, and workload failures across the cluster at scale. Build repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms.

Tune runtime settings, communication parameters, and deployment configurations in close partnership with framework, systems, and platform teams. Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization. Mentor engineers, drive technical standards, and act as a force multiplier across the broader performance and infrastructure organization.

What we need to see: Bachelor's or Master's in Computer Science or a related technical field (or equivalent experience). 8+ years of experience developing software infrastructure for large-scale AI or HPC systems, including a track record of technical leadership. Expertise debugging and triaging AI applications across the full stack - from the application layer down to the hardware.

Deep hands-on experience with NCCL, CUDA-aware distributed execution, and debugging multi-GPU and multi-node workloads at scale. Proven track record of architecting, debugging, and scaling large-scale distributed systems. Expert-level Python and C/C++ programming skills.

Experience operating workloads in scheduled, containerized cluster environments. Excellent analytical, debugging, and communication skills, with the ability to influence across teams. Ways to stand out from the crowd: Demonstrated experience debugging and optimizing AI workloads at large scale.

Deep familiarity with the RDMA software stack (NCCL, IB verbs, UCX, libfabric). Strong knowledge of GPU cluster fabrics and topology, including NVLink, NVSwitch, PCIe, RoCE, and InfiniBand. Experience building acceptance tests, benchmark harnesses, regression gates, or cluster qualification tooling for AI platforms.

Experience building resilience, fault-detection, or failure-attribution systems for datacenter-scale infrastructure. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us.

If you're creative, autonomous, and love a challenge, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until June 8, 2026. This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US