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Remote Audio Signal Processing Machine Learning Jobs in Nevada

Motional

Machine Learning Systems Engineer

Las Vegas, NV · On-site +1

$144K - $192K/yr

... fundamental machine learning concepts, architectures, and processes. * Problem Solving ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

TensorWave

Senior Machine Learning Engineer

Las Vegas, NV · On-site +1

$117K - $154K/yr

About the Role We're looking for a Senior Machine Learning Engineer to join our team during an ... If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.

Motional

Senior Embedded Software Engineer

Las Vegas, NV · On-site +1

$118K - $155K/yr

... machine learning, sensors, and hardware compute platforms to evolve Motional's next-generation on ... vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.

micro1 AI

Domain Expert - (STEM PhD)

Las Vegas, NV · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

micro1 AI

Engineering AI Evaluator (PhD)

Las Vegas, NV · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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All JobsAudio Signal Processing Machine Learning JobsRemote Audio Signal Processing Machine Learning JobsRemote Audio Signal Processing Machine Learning Jobs in Nevada

Remote Audio Signal Processing Machine Learning information

What is the difference between Remote Audio Signal Processing Machine Learning vs Remote Audio Engineering?

AspectRemote Audio Signal Processing Machine LearningRemote Audio Engineering
Required CredentialsKnowledge of machine learning, signal processing, programming (Python, MATLAB)Audio engineering certifications, audio production experience
Work EnvironmentResearch labs, tech companies, remote collaborationRecording studios, broadcast companies, remote or onsite
Industry UsageDeveloping algorithms for audio enhancement, noise reduction, speech recognitionMixing, mastering, live sound, audio content creation

Remote Audio Signal Processing Machine Learning focuses on developing algorithms using machine learning techniques to improve audio quality and analysis. In contrast, Remote Audio Engineering involves practical audio production, mixing, and recording tasks. Both roles require audio knowledge, but the former emphasizes programming and data science, while the latter centers on sound quality and production skills.

What are popular job titles related to Remote Audio Signal Processing Machine Learning jobs in Nevada? For Remote Audio Signal Processing Machine Learning jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Remote Audio Signal Processing Machine Learning jobs in Nevada look for? The top searched job categories for Remote Audio Signal Processing Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for Remote Audio Signal Processing Machine Learning jobs? Cities in Nevada with the most Remote Audio Signal Processing Machine Learning job openings:
Remote Audio Signal Processing Machine Learning jobs near you
Infographic showing various Remote Audio Signal Processing Machine Learning job openings in Nevada as of July 2026, with employment types broken down into 76% Full Time, 20% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Machine Learning Systems Engineer

Machine Learning Systems Engineer

Motional

Las Vegas, NV • On-site, Remote

Other

Re-posted 3 days ago

Job description

Mission Summary:

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models.

What you'll be doing:

  • Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
  • Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed.
  • Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.
  • Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput.

What we're looking for:

  • Education: Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline.
  • Software Engineering: Strong proficiency in Python.
  • ML Frameworks: Extensive hands-on experience with PyTorch.
  • ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.
  • Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges.

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

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