Torrance, CA

Salary
Posted
Jul 22, 2026
Location
Torrance, CA
Last confirmed open
Jul 23, 2026

What this job asks for AI summary

This role sits at the core of an AI-driven weather forecasting platform, bridging raw sensor data and production forecast APIs. The work involves building and optimizing GPU kernels, distributed training pipelines, and cloud-native infrastructure to run physics-aware deep learning models at scale, as well as converting research prototypes into production code. It suits a senior engineer with hands-on experience in high-performance computing, large-scale distributed ML, and cloud infrastructure.

Senior level · 5+ years · Los Angeles-Long Beach-Anaheim, CA · Bachelor's required · Full-time

Must have (8)
Python, C++ or Rust · 5+ yrsCUDAJAX, PyTorch or TensorFlowGCP, AWS or AzureKubernetes, Ray or SlurmCI/CDcontainerizationdistributed training
Nice to have (5)
numerical weather predictionremote sensinggeospatial intelligencephysics-informed MLdata assimilation

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

Roughly 110 people in the Los Angeles-Long Beach-Anaheim, CA area plausibly meet what this posting asks for (software developers). range 30–190

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What gives you an edge
CUDA4%JAX9%PyTorch9%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python51%C++51%Rust51%CI/CD45%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $164,459 (middle half $130,334–$195,752).

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (11)

The role sits at the intersection of high-performance ML infrastructure engineering and scientific computing/AI modeling, making it a genuine toss-up between Software Developers (15-1252) and Data Scientists (15-2051). The primary day-to-day emphasis on CUDA kernels, distributed training pipelines, and production infrastructure tips it toward 15-1252.

The 5+ years requirement is stated against 'writing high-performance Python/C++/Rust for GPU workloads' — treated as the role-level experience floor (the overall years minimum of 5) as well as the years demanded on the language skill group.

Python, C++, and Rust are listed together as a single language requirement ('Python/C++/Rust'); they are emitted as separate skills with each other as alternatives, reflecting that fluency in at least one is the gate.

JAX, PyTorch, and TensorFlow are listed as interchangeable deep learning framework options ('JAX, PyTorch, TensorFlow, etc.'); JAX and PyTorch appear in the job description narrative as primary examples and are marked required; TensorFlow is the named third option and is marked preferred to reflect the 'etc.' open-endedness.

GCP, AWS, and Azure are listed as interchangeable cloud platforms; one is required.

Ray, Kubernetes, and Slurm are listed as pipeline orchestration options ('Ray, Kubernetes, Slurm, or similar'); Kubernetes is marked required as the canonical representative of the gate, with Ray and Slurm as alternatives. Ray and Slurm are also emitted separately as preferred to surface them individually.

Containerization and CI/CD are stated under the required DevOps section without naming a specific tool (Docker, GitHub Actions, etc.), so they are captured at the concept level as named in the JD.

Distributed training at scale (100+ GPU) is a hard gate stated in Requirements; it is captured as a required skill since no single named tool is specified.

Bonus Qualifications (numerical weather prediction, remote sensing, geospatial intelligence, physics-informed ML, data assimilation) are all listed under an explicit 'Bonus Qualifications' heading and are marked preferred.

The posting states 'LA HQ required,' confirming on-site presence in Los Angeles; remote=false.

No compensation figures are provided; salary is described only as 'competitive.'

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