ZipRecruiter

Log In

1

Tensor Jobs in California (NOW HIRING)

Nastech Global

AI Researcher

Mountain View, CA · On-site

Torch, Tensor Flow Experience in Visual SLAM (Simultaneous Localization and Mapping), YOLO, Faster R CNN and deep learning models Knowledge of NVIDIA ISSAC Sim, Omniverse to develop the models Basic ...

Qualcomm

Sr. Staff Software Engineer

San Diego, CA · On-site

$130K - $171K/yr

Strong experience with AI and GenAI inference frameworks including Py-Torch, TensorFlow, ONNX Runtime, and Llama CPP, with solid understanding of AI fundamentals, model architectures, tensor layouts ...

Anthropic

Performance Engineer, GPU

San Francisco, CA · On-site

Your work will span the entire stack-from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering ...

Baseten

Post-Training Research Engineer

San Francisco, CA · On-site

$200K - $275K/yr

Advanced experience in a tensor/array computation library like PyTorch, TensorFlow, Jax, or similar * A detailed understanding of transformer training parallelism strategies like data parallelism ...

Quadric

AI Performance Modeling Engineer

Burlingame, CA · On-site

$180 - $225/hr

Model tensor placement, tiling across processing elements, local memory residency, and data movement across memory tiers. * Model sharding and collective boundary communication across multi-die ...

previous page

Showing results 41-60

All JobsTensor JobsTensor Jobs in California

Tensor information

See California salary details

$45.4K

$162.9K

$240.3K

How much do tensor jobs pay per year?

As of Aug 22, 2026, the average yearly pay for tensor in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

What is a tensor?

A Tensor job typically refers to a role involving tensors, which are mathematical objects used in machine learning, AI, and scientific computing. These jobs often require expertise in deep learning frameworks like TensorFlow or PyTorch, where tensors represent multi-dimensional arrays for data processing. A Tensor job can involve designing and optimizing neural networks, performing large-scale data analysis, or working with high-performance computing.

What are the key skills and qualifications needed to thrive as a tensor?

I'm sorry, but 'Tensor' is not recognized as a real-world professional occupation.

What are some common challenges faced by TensorFlow developers when working on large-scale machine learning projects?

TensorFlow Developers often encounter challenges such as optimizing model performance for large datasets, managing distributed training across multiple GPUs or TPUs, and ensuring reproducibility of experiments. Collaboration with data engineers and DevOps teams is essential to streamline data pipelines and deployment workflows. Staying up to date with frequent updates in the TensorFlow ecosystem and best practices for model optimization is also crucial for success in this role.

What is the difference between Tensor vs Data Scientist?

AspectTensorData Scientist
Required CredentialsKnowledge of machine learning, programming skills, often a degree in computer science or related fieldsDegree in statistics, computer science, or related fields; strong analytical skills
Work EnvironmentTech companies, AI research labs, software development teamsBusiness, finance, healthcare, and tech industries analyzing data to inform decisions
Industry UsagePrimarily in AI, machine learning, and deep learning projectsAcross industries for data analysis, predictive modeling, and insights

While a Tensor is a fundamental data structure used in machine learning frameworks like TensorFlow, a Data Scientist analyzes data to extract insights and build models. Tensors are tools that Data Scientists often work with, but they are not roles themselves. Understanding tensors is essential for Data Scientists involved in AI and machine learning projects.

What are popular job titles related to Tensor jobs in California?

For Tensor jobs in California, the most frequently searched job titles are:

What job categories do people searching Tensor jobs in California look for?

The top searched job categories for Tensor jobs in California are:

What cities in California are hiring for Tensor jobs?

Cities in California with the most Tensor job openings:

Tensor jobs near you
Infographic showing various Tensor job openings in California as of August 2026, with employment types broken down into 1% Internship, 97% Full Time, and 2% Contract. Highlights an 74% Physical, 10% Hybrid, and 16% Remote job distribution, with an average salary of $162,857 per year, or $78.3 per hour.

Research Scientist / Engineer - Performance Optimization

Luma

Redwood City, CA • On-site

$251K/yr

Full-time

Posted yesterday

New

Job description

You'll make Luma's multimodal models fast - profiling and optimizing GPU, CPU, and accelerator code so they train efficiently and deploy at scale without sacrificing quality. You'll write the kernels and operations that get the most out of the hardware.
This is deep performance work: fused kernels, tensor cores, Triton and CUDA, distributed multi-node deployment. It fits someone with expert GPU-optimization skills and a deep understanding of transformer internals. If you're not at home in CUDA, Triton, and profilers, this is the wrong depth.
What You'll Own
  • Profile and optimize GPU/CPU/accelerator code for maximum utilization and minimal latency.
  • Write high-performance PyTorch, Triton, and CUDA, dropping to custom operations when needed.
  • Develop fused kernels and leverage tensor cores and modern hardware features across platforms.
  • Optimize model architectures and implementations for distributed multi-node production deployment.
  • Build performance monitoring and analysis tools and automation.
  • Research and implement cutting-edge optimization techniques for transformer models.

First 90 Days
One way the first 90 could unfold.
  • Days 1-30 - Immerse & Diagnose: Profile the current training and inference paths and find the biggest performance wins.
  • Days 30-60 - Ship & Validate: Land a kernel or architecture optimization that measurably improves utilization or latency.
  • Days 60-90 - Scale & Systemize: Build the monitoring and automation that keeps performance gains from regressing.

What You Bring
  • Expert-level Triton/CUDA programming and GPU optimization.
  • Strong PyTorch skills, including kernel development and custom operations.
  • Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling).
  • Deep understanding of transformer architectures and attention mechanisms.

Nice to Have
  • Experience with compilers and exporters (torch.compile, TensorRT, ONNX, XLA).
  • Experience optimizing inference workloads for latency and throughput.
  • Triton compiler and kernel fusion techniques.
  • Knowledge of warp-level intrinsics and advanced CUDA optimization.

About Luma: Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world. We believe multimodality is critical for intelligence - the next step beyond language models comes from vision. Luma is an equal opportunity employer.
Luma logo

About Luma

Sourced by ZipRecruiter

Industry

Arts, entertainment, and recreation

Company size

201 - 500 Employees

Headquarters location

Santa Monica, CA, US

Year founded

2002

View All Luma Jobs

Apply