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T R Frameworks Jobs in California (NOW HIRING)

Forsys Inc.

Business Architect, Lead-to-Cash

Milpitas, CA

$63 - $86.25/hr

Develop internal best practices, reusable L2C frameworks, and mentor mid-level consultants ... Regards, Amar Tel: +1 7 3 2 8 2 3 4 3 0 4 a m a r . b h u p a t h i @ f o r s y s i n c . c o m ...

AHMC Healthcare

Technician, Radiology

Whittier, CA · On-site

Completes annual safety updates within established time frames. * Completes general and ... R.T required; C.R.T. license required. BLS certification required. Fluoroscopy Permit required ...

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T R Frameworks information

What are the key skills and qualifications needed to thrive as a TR Frameworks specialist, and why are they important?

To thrive as a TR Frameworks specialist, you need a strong understanding of technical architecture, programming principles, and experience with frameworks such as .NET, Spring, or Django, typically supported by a relevant computer science degree. Familiarity with version control systems, continuous integration tools, and cloud platforms is often required, along with certifications like AWS Certified Developer or Microsoft Certified: Azure Developer Associate. Excellent problem-solving skills, attention to detail, and effective communication set top candidates apart in this role. These skills and qualities ensure robust framework development, smooth project delivery, and effective collaboration within software development teams.

What are T R Frameworks?

T R Frameworks typically refers to frameworks used for Test and Release (T&R) processes in software development. These frameworks provide structured methods and tools for automating the testing and release cycles, ensuring software quality and timely deployment. They can include tools for unit testing, integration testing, continuous integration, and automated deployment. Common T&R frameworks include Jenkins, Travis CI, and others that help streamline the development workflow and reduce human error. Their use is critical in modern DevOps practices.

What is the difference between T R Frameworks vs Market Research Analyst?

AspectT R FrameworksMarket Research Analyst
Required CredentialsTypically requires certifications in project management or specific frameworksBachelor's degree in marketing, statistics, or related field; often requires analytical skills certifications
Work EnvironmentConsulting firms, project-based settings, client sitesCorporate offices, research firms, marketing departments
Industry UsageUsed across consulting, project management, and strategic planningPrimarily in marketing, advertising, and consumer insights
Common Search/ComparisonOften compared for strategic and project management rolesCompared for market analysis and consumer research roles

While T R Frameworks focus on applying structured methodologies for project and strategic management, Market Research Analysts specialize in gathering and analyzing consumer data to inform marketing strategies. Both roles require analytical skills but serve different functions within organizations.

How do professionals working with T R Frameworks typically collaborate with cross-functional teams?

Professionals utilizing T R Frameworks often work closely with developers, testers, and product managers to ensure seamless integration and implementation of robust testing methodologies. Collaboration usually involves regular meetings to align on project goals, sharing best practices for test automation, and troubleshooting issues as they arise. Effective communication and a proactive approach to knowledge sharing are essential, as they help maintain high-quality standards and foster a culture of continuous improvement within the team.
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What job categories do people searching T R Frameworks jobs in California look for? The top searched job categories for T R Frameworks jobs in California are:
What cities in California are hiring for T R Frameworks jobs? Cities in California with the most T R Frameworks job openings:
T R Frameworks jobs near you
Infographic showing various T R Frameworks job openings in California as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Staff GPU Systems Engineer, Space Computing

Staff GPU Systems Engineer, Space Computing

Relativity Space

Long Beach, CA

Full-time

PTO

Posted 16 days ago

Job description

At Relativity Space, we're building rockets to serve today's needs and tomorrow's breakthroughs. Our Terran R vehicle will deliver customer payloads to orbit, meeting the growing demand for launch capacity. But that's just the start. Achieving commercial success with Terran R will unlock new opportunities to advance science, exploration, and innovation, pioneering progress that reaches beyond the known.

Joining Relativity means becoming part of something where autonomy, ownership, and impact exist at every level. Here, you're not just executing tasks; you're solving problems that haven't been solved before, helping develop a rocket, a factory, and a business from the ground up. Whether you're in propulsion, manufacturing, software, avionics, or a corporate function, you'll collaborate across teams, shape decisions, and see your work come to life in record time. Relativity is a place where creativity and technical rigor go hand in hand, and your voice will help define the stories we're writing together. Now is a unique moment in time where it's early enough to leave your mark on the product, the process, and the culture, but far enough along that Terran R is tangible and picking up momentum. The most meaningful work of your career is waiting. Join us.

About the Team:

The Interplanetary Sciences Program was established to expand access to scientific exploration across our solar system. Its mission is to make planetary research faster, more affordable, and more capable than ever before by rethinking how science missions are designed, built, and operated. The program aims to enable scientists to send instruments to distant worlds without decades of development or prohibitive costs. By creating a sustainable model for interplanetary exploration, we are transforming space science from an occasional event into a continuous process of discovery that accelerates knowledge, broadens participation, and inspires the next generation of explorers.

About the Role:

  • Own the GPU compute environment for a space-based data center — setup, driver integration, container runtime, job scheduling, and performance optimization — building the platform that enables onboard AI/ML inference and SAR reprocessing millions of miles from the nearest sysadmin
  • Profile and optimize compute performance across the full stack: GPU utilization, memory bandwidth, I/O throughput, and storage interface performance, squeezing maximum science return from constrained power and thermal budgets that shift between sunlit burst processing and eclipse idle periods
  • Build power and thermal-aware compute scheduling that orchestrates batch workloads around orbital constraints, coordinating with the storage platform to sustain 10 Gbps data movement between NAS and compute nodes during processing windows
  • Develop compute health monitoring and upset recovery mechanisms — checkpoint/restart strategies, GPU fault detection, and automated recovery — so a radiation-induced upset means a restarted job, not a lost processing window
  • Integrate GPU drivers with the payload Linux image in coordination with the Platform RE, manage the container runtime for compute workloads, and ensure the platform reliably runs ML frameworks and SAR processing pipelines maintained by the broader operations team

About You:

  • BS/MS in Computer Science or Electrical Engineering and 5+ years of relevant experience
  • Hands-on experience with GPU programming and compute frameworks — CUDA, ROCm, or OpenCL — with real performance profiling and optimization work, not just running tutorials
  • Strong Linux systems administration and performance tuning skills: you've diagnosed I/O bottlenecks, tuned memory management, and understood why a workload isn't hitting expected throughput
  • Experience with container technologies (Docker, Podman, or lightweight alternatives) and HPC job scheduling concepts
  • Working proficiency in Python for tooling, scripting, and ML framework integration, with C/C++ skills for performance-critical system components

Nice to haves but not required:

  • Experience with HPC cluster administration, ML infrastructure, or cloud GPU compute platforms at scale
  • Deep familiarity with ML framework runtime requirements — PyTorch or TensorFlow deployment, model serving, and inference optimization
  • Knowledge of GPU compute architectures at the hardware level: CUDA cores, compute units, memory hierarchies, and how they affect real workload performance
  • Experience with high-throughput data movement and storage I/O optimization — NFS tuning, buffer management, and sustaining multi-gigabit throughput
  • Background in power-managed computing: duty cycling, thermal throttling, and workload scheduling under variable power constraints
  • Experience designing checkpoint/restart or fault-tolerant batch processing systems — space experience not required, similar problems exist in large-scale distributed infrastructure and autonomous systems

At Relativity Space, we are committed to transparency and fairness in our compensation practices. Actual compensation will be determined based on experience, qualifications, and other job-related factors.
Compensation is only one part of our total rewards package. Relativity Space offers competitive salary and equity, a generous PTO and sick leave policy, parental leave, an annual learning and development stipend, and more! To see some of the benefits & perks we offer, please visit here.

Hiring Range:
$181,000—$248,500 USD

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

If you need a reasonable accommodation, please contact us at accommodations@relativityspace.com.