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Remote Audio Machine Learning Jobs in Nevada (NOW HIRING)

Motional

Staff Machine Learning Engineer

Las Vegas, NV · On-site +1

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

Motional

Machine Learning Systems Engineer

Las Vegas, NV · On-site +1

$144K - $192K/yr

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

Maximus

AI/ML Software Developer

Las Vegas, NV · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

Maximus

AI/ML Software Developer

Sparks, NV · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

Maximus

AI/ML Software Developer

Henderson, NV · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

Maximus

AI/ML Software Developer

Carson City, NV · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

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Remote Audio Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Audio Machine Learning Engineer, and why are they important?

To thrive as a Remote Audio Machine Learning Engineer, you need strong foundations in digital signal processing, machine learning algorithms, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, and audio processing libraries (e.g., LibROSA), as well as experience with cloud platforms, is highly valuable. Excellent problem-solving skills, self-motivation, and clear remote communication are essential soft skills for collaborating across distributed teams. These competencies enable the development of robust, innovative audio ML solutions while ensuring effective teamwork and project delivery in a remote setting.

How does a Remote Audio Machine Learning role typically collaborate with cross-functional teams, and what communication tools are commonly used?

In a Remote Audio Machine Learning position, collaboration with cross-functional teams such as software engineers, data scientists, and product managers is essential. Regular communication is maintained through tools like Slack, Zoom, and project management platforms such as Jira or Trello. Team members often participate in virtual stand-ups, sprint planning sessions, and code reviews to ensure alignment on project goals and timelines. Effective asynchronous communication and clear documentation are especially important in remote settings to keep everyone informed and foster a productive workflow.

What is a Remote Audio Machine Learning job?

A Remote Audio Machine Learning job involves using machine learning techniques to analyze, process, or generate audio data while working from a remote location. Professionals in this field develop algorithms for tasks such as speech recognition, music classification, noise reduction, or audio synthesis. They often work with large datasets, build and train models, and collaborate with teams online. These roles typically require skills in programming, signal processing, and experience with machine learning frameworks.

What is the difference between Remote Audio Machine Learning vs Remote Audio Engineer?

AspectRemote Audio Machine LearningRemote Audio Engineer
Required CredentialsBackground in machine learning, data science, or AI; often a degree in computer science or related fieldsAudio engineering, sound design, or music production degree or certification
Work EnvironmentPrimarily focused on developing algorithms, data analysis, and model training, often in a tech or research settingRecording, mixing, editing audio, often in studios or remote production setups
Employer & Industry UsageTech companies, research labs, AI startups working on audio recognition or enhancementMusic, film, broadcasting, and media production companies

Remote Audio Machine Learning specialists focus on developing algorithms to process and analyze audio data, while Remote Audio Engineers handle the practical aspects of recording and editing sound. Both roles may collaborate but serve different functions within the audio industry.

What are the most commonly searched types of Audio Machine Learning jobs in Nevada? The most popular types of Audio Machine Learning jobs in Nevada are:
What are popular job titles related to Remote Audio Machine Learning jobs in Nevada? For Remote Audio Machine Learning jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Remote Audio Machine Learning jobs in Nevada look for? The top searched job categories for Remote Audio Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for Remote Audio Machine Learning jobs? Cities in Nevada with the most Remote Audio Machine Learning job openings:
Remote Audio Machine Learning jobs near you
Machine Learning Systems Engineer

Machine Learning Systems Engineer

Motional

Las Vegas, NV • On-site, Remote

Other

Posted 19 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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