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Tensor Jobs in California (NOW HIRING)

About the role Own verification of our AI compute core - tensor pipelines, MAC arrays, accumulator logic, and the compute memory interconnect. Work with chip-design and software teams driving ...

Lead the definition of mechanisms for efficient movement of tensor activations, weights, and outputs through on-chip and off-chip memory pathways and high-throughput DMA architecture. * Partner ...

Lead the definition of mechanisms for efficient movement of tensor activations, weights, and outputs through on-chip and off-chip memory pathways and high-throughput DMA architecture. * Partner ...

AI Core DV Engineer

Mountain View, CA · On-site

$180K - $320K/yr

About the role Own verification of our AI compute core - tensor pipelines, MAC arrays, accumulator logic, and the compute ↔ memory interconnect. Work with chip-design and software teams driving ...

AI Core DV Engineer

Mountain View, CA · On-site

$180K - $320K/yr

About the role Own verification of our AI compute core - tensor pipelines, MAC arrays, accumulator logic, and the compute ↔ memory interconnect. Work with chip-design and software teams driving ...

Showing results 21-40

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 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:

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.

Kernel Engineer (Compute / Accelerator)

DensityAI

Mountain View, CA • On-site

Full-time

Re-posted 20 days ago


Job description

Job Summary:
DensityAI is a company focused on AI technology, and they are seeking a Kernel Engineer to write and optimize compute kernels for a custom AI accelerator. The role involves collaborating with architecture and compiler teams to ensure high performance of ML workloads on hardware.
Responsibilities:
• Write and optimize compute kernels for a custom AI accelerator — tensor operations, data movement patterns, memory hierarchy exploitation
• Develop and maintain profiling infrastructure to measure kernel performance against architectural targets
• Define and document shuffle patterns for ML kernel primitives across CPU-like control, tensor cores, and CUTLASS-style operations
• Drive kernel DSL design decisions — thread spawn mechanisms, register passing conventions, and memory management strategies
• Enable end-to-end kernel execution on the architectural simulator
• Collaborate with the compiler team on the MLIR dialect — your kernels are the primary validation target
• Create onboarding documentation and kernel writing guides for the broader team
Qualifications:
Required:
• C/C++ — production-grade systems code, not scripted glue. You'll write performance-critical kernels.
• CUDA or equivalent accelerator programming — deep experience writing GPU kernels, understanding warp/wavefront execution, memory coalescing, shared memory optimization. The mental model transfers directly.
• Computer architecture — you need to reason about pipelines, memory hierarchies, data movement costs, and how software maps to hardware.
• Performance profiling and optimization — you live in profilers. Identifying bottlenecks, measuring throughput, and iterating until kernels meet targets is the core loop.
• Tensor operations — practical understanding of GEMM, convolution, attention, reduction, and scatter/gather as they map to hardware.
• Python — for scripting, DSL integration, and profiling automation.
Preferred:
• RISC-V, x86, or ARM64 ISA experience
• MLIR or LLVM compiler infrastructure
• HPC or scientific computing background (large-scale parallel compute intuition)
• FPGA or Verilog/SystemVerilog (ability to read RTL and reason about the hardware you're targeting)
• Familiarity with CUTLASS, Triton, or similar kernel libraries
Company:
DensityAI is an infrastructure for data centers serving automotive, robotics, and industrial applications Founded in 2025, the company is headquartered in Mountain View, USA, with a team of 51-200 employees. The company is currently Early Stage.