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Learning Systems Jobs in Texas (NOW HIRING)

This role owns TOCA's learning systems, content strategy, and training experience across the U.S. and Canada-ensuring teammates have access to clear, engaging, and up-to-date learning that drives ...

This role owns TOCA's learning systems, content strategy, and training experience across the U.S. and Canada-ensuring teammates have access to clear, engaging, and up-to-date learning that drives ...

This role owns TOCA's learning systems, content strategy, and training experience across the U.S. and Canada--ensuring teammates have access to clear, engaging, and up-to-date learning that drives ...

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Learning Systems information

What is the difference between Learning Systems vs Instructional Designer?

AspectLearning SystemsInstructional Designer
Required CredentialsTypically a degree in education, instructional technology, or related field; certifications in LMS platformsDegree in education, instructional design, or related; certifications in instructional design tools
Work EnvironmentEducational institutions, corporate training departments, e-learning companiesEducational institutions, corporate training, e-learning development firms
Employer & Industry UsageUsed by organizations implementing LMS platforms for trainingHired to design and develop instructional content and courses

Learning Systems professionals focus on managing and implementing Learning Management Systems (LMS), ensuring effective delivery of online training. Instructional Designers create engaging educational content and course materials. While both roles support e-learning, Learning Systems specialists handle platform administration, whereas Instructional Designers develop instructional content.

What are learning systems?

Learning systems are software platforms or tools designed to facilitate, manage, and track educational or training activities. They are commonly used in schools, universities, and organizations to deliver online courses, assessments, and learning resources. Learning systems often include features such as course management, progress tracking, and communication tools to enhance the teaching and learning experience. Examples include Learning Management Systems (LMS) like Moodle, Canvas, and Blackboard. These systems support both instructors and learners by providing a centralized platform for e-learning.

How does a Learning Systems professional typically collaborate with faculty and IT teams to implement new educational technologies?

Learning Systems professionals often serve as the bridge between academic faculty and IT departments, working closely with both to ensure successful adoption of new educational technologies. They translate instructional needs into technical requirements, assist faculty with integrating tools into courses, and coordinate with IT for system configuration and troubleshooting. Regular communication and training sessions are common, as is ongoing support to address technical or pedagogical challenges. This collaborative approach helps maximize the effectiveness and user adoption of learning platforms across the institution.

What are the key skills and qualifications needed to thrive as a Learning Systems Specialist, and why are they important?

To thrive as a Learning Systems Specialist, you need expertise in instructional design, e-learning principles, and a relevant degree in education, instructional technology, or a related field. Familiarity with Learning Management Systems (LMS) like Moodle, Blackboard, or Canvas, as well as certification in platforms such as SCORM or xAPI, is typically required. Strong problem-solving, communication, and project management skills help you collaborate with educators and troubleshoot technical issues. These skills ensure effective delivery, maintenance, and continuous improvement of digital learning solutions that support organizational training goals.
Infographic showing various Learning Systems job openings in Texas as of May 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.
Senior Software Engineer, CUDA Deep Learning Systems

Senior Software Engineer, CUDA Deep Learning Systems

NVIDIA

Austin, TX • On-site

$121K - $160K/yr

Full-time

Posted 24 days ago


Job description

Job Summary:
NVIDIA is a leading technology company focused on pioneering initiatives in artificial intelligence and deep learning systems. They are seeking a Senior Software Engineer to work on optimizing CUDA and Deep Learning Systems, exploring novel systems optimizations, and collaborating with AI researchers to enhance hardware performance for AI workloads.
Responsibilities:
• Explore, research, and prototype novel systems optimizations for advanced deep learning models at the intersection of high-level DL frameworks and low-level CUDA through modeling, simulation, and silicon prototyping.
• Architect and optimize distributed computing systems that scale seamlessly from a single node to massive, cluster-scale supercomputing environments.
• Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads.
• Analyze complex hardware-software interactions to identify and resolve performance bottlenecks in both training and inference pipelines.
• Collaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and algorithms that improve accelerator compute utilization, memory bandwidth, cross-node network communication efficiency and programmability.
• Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.
• Write clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products.
Qualifications:
Required:
• BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
• 8+ years of relevant industry experience or equivalent academic experience after degree achievement.
• Strong proficiency in C++ and Python programming.
• Solid background in the fundamentals of Deep Learning with a focus on transformers.
• Strong understanding of distributed computing principles, multi-node scaling, and the unique performance challenges of cluster-scale execution.
• Proven experience in systems programming, computer architecture, and low-level systems performance optimization.
• Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience with CUDA programming and kernel optimization.
• A strong analytical approach with experience using profiling tools to deeply understand software performance on hardware.
• Experience profiling and optimizing innovative vision models, generative AI architectures, or diffusion models.
• Background in deep learning compilers, both graph-level and codegen (e.g., Triton, XLA, torch compile)
Preferred:
• Deep expertise in the performance internals and execution graphs of major deep learning autograd, training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron, MaxText, etc.).
• Hands-on experience with CUDA, communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline parallelism, tensor parallelism).
• Knowledge of numerical methods, low-precision arithmetic (e.g., NVFP4, MXFP4, FP8, INT8), and their implications on deep learning model accuracy and performance.
• Familiarity with systems requirements for Reinforcement Learning (RL) or highly parallel simulation environments and/or research background in machine learning systems or adjacent fields.
• Experience with machine learning, especially agentic systems, applied to systems problems.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

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

Year founded

1993