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Trt Jobs in California (NOW HIRING)

ARRT Radiation Therapy Certification (ARRT-T) - Required Therapeutic Radiologic Technology (TRT/RTT) Certification - Required BLS/CPR Certification - Preferred Fluoroscopy Permit - Preferred Job ...

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Trt information

See California salary details

$30

$61

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How much do trt jobs pay per hour?

As of Aug 31, 2026, the average hourly pay for trt in California is $61.29, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $70.24 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the trt position, and why are they important?

To excel as a TRT (Transitional Return to Work) Specialist, you need a strong understanding of workers' compensation, occupational health, and disability management, often complemented by certifications in case management or human resources. Familiarity with case management software, claims processing systems, and relevant legal or regulatory guidelines is essential for success. Excellent communication, negotiation, and problem-solving skills are vital in collaborating with employees, healthcare providers, and employers. These competencies enable effective coordination of return-to-work programs, ensuring both compliance and supportive reintegration for employees.

What are some typical challenges faced by a trt specialist, and how are they addressed?

TRT Specialists often navigate challenges such as coordinating between multiple stakeholders, accommodating varying medical restrictions, and ensuring regulatory compliance. To address these obstacles, they rely on strong organizational skills, up-to-date knowledge of industry guidelines, and clear communication across teams. They also develop tailored return-to-work plans and monitor employee progress closely, making adjustments as needed to support a smooth transition. As a result, proactive problem-solving and flexibility are highly valued in this role to achieve successful outcomes for both employees and employers.

Infographic showing various Trt job openings in California as of August 2026, with employment types broken down into 53% Full Time, 12% Part Time, and 35% Contract. Highlights an 100% In-person job distribution, with an average salary of $127,492 per year, or $61.3 per hour.

Senior Deep Learning Software Engineer, Inference and Model Optimization

Nvidia

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Re-posted 2 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies


Job description

NVIDIA is at the forefront of the generative AI revolution! The Algorithmic Model Optimization Team specifically focuses on optimizing generative AI models such as large language models (LLM) and diffusion models for maximal inference efficiency using techniques ranging from neural architecture search and pruning to sparsity, quantization, and automated deployment strategies. Our work includes conducting applied research to improve model efficiency as well as developing an innovative software platform (TRT Model Optimizer). Our software is used both internally across NVIDIA and externally by research and engineering teams alike developing best-in-class AI models.

We are now looking for a Senior Deep Learning Software Engineer to develop and scale up our automated inference and deployment solution. As part of the team, you will be instrumental in pushing the limits of inference efficiency and large-scale, automated deployment. Your work will touch upon fundamental aspects of a typical machine learning stack including working in high-level frameworks like PyTorch and HuggingFace to developing and improving high-performance kernel implementations in CUDA, TRT-LLM, and Triton. This is an exceptional opportunity for passionate software engineers straddling the boundaries of research and engineering, with a strong background in both machine learning fundamentals and software architecture & engineering.

What you'll be doing:

  • Train, develop, and deploy state-of-the generative AI models like LLMs and diffusion models using NVIDIA's AI software stack.

  • Leverage and build upon the torch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile, etc...) to analyze and extract standardized model graph representation from arbitrary torch models for our automated deployment solution.

  • Develop high-performance optimization techniques for inference, such as automated model sharding techniques (e.g. tensor parallelism, sequence parallelism), efficient attention kernels with kv-caching, and more.

  • Collaborate with teams across NVIDIA to use performant kernel implementations within our automated deployment solution.

  • Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities.

  • Continuously innovate on the inference performance to ensure NVIDIA's inference software solutions (TRT, TRT-LLM, TRT Model Optimizer) can maintain and increase its leadership in the market.

  • Play a pivotal role in architecting and designing a modular and scalable software platform to provide an excellent user experience with broad model support and optimization techniques to increase adoption.

What we need to see:

  • Masters, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related field.

  • 5+ years of relevant work or research experience in Deep Learning.

  • Excellent software design skills, including debugging, performance analysis, and test design.

  • Strong proficiency in Python, PyTorch, and related ML tools (e.g. HuggingFace).

  • Strong algorithms and programming fundamentals.

  • Good written and verbal communication skills and the ability to work independently and collaboratively in a fast-paced environment.

Ways to stand out from the crowd:

  • Contributions to PyTorch, JAX, or other Machine Learning Frameworks.

  • Knowledge of GPU architecture and compilation stack, and capability of understanding and debugging end-to-end performance.

  • Familiarity with NVIDIA's deep learning SDKs such as TensorRT.

  • Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Increasingly known as "the AI computing company" and widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Are you creative, motivated, and love a challenge? If so, we want to hear from you! Come, join our model optimization group, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly-growing field.

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 August 28, 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


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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