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Remote Battery Systems Engineer Jobs in Nevada (NOW HIRING)

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 ...

Quora

$139K - $168K/yr

Improve our existing Machine Learning systems using your expertise * Identify new opportunities to ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Improve our existing Machine Learning systems using your expertise * Identify new opportunities to ... LI-SS2 LI-REMOTE

New

Quora

$139K - $168K/yr

Improve our existing Machine Learning systems using your expertise * Identify new opportunities to ... LI-SS2 LI-REMOTE

Quora

$202K - $234K/yr

Develop and maintain internal tools and systems that automate existing work and increase employee ... Experience creating LLM-backed tools involving prompt engineering and automated evals * 5+ years of ...

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Remote Battery Systems Engineer information

What does a Remote Battery Systems Engineer do?

A Remote Battery Systems Engineer is responsible for designing, testing, and managing battery systems for various applications, such as electric vehicles, renewable energy storage, or consumer electronics, while working remotely. They focus on optimizing battery performance, ensuring safety, and integrating battery technology with other hardware and software systems. Their job may also involve analyzing data, troubleshooting issues, and collaborating with cross-functional teams using virtual communication tools.

What are the key skills and qualifications needed to thrive as a Remote Battery Systems Engineer, and why are they important?

To thrive as a Remote Battery Systems Engineer, you need a solid background in electrical engineering, battery chemistry, and energy storage systems, typically supported by a relevant engineering degree. Familiarity with battery management systems (BMS), simulation software (like MATLAB/Simulink), and industry certifications such as IEEE or SAE standards is often required. Strong analytical thinking, effective remote communication, and problem-solving skills help you excel in a distributed work environment. These skills and tools are critical for designing, optimizing, and troubleshooting battery systems safely and efficiently from a remote setting.

What are the typical challenges faced by a Remote Battery Systems Engineer when collaborating with cross-functional teams?

As a Remote Battery Systems Engineer, one common challenge is maintaining clear and consistent communication with cross-functional teams, such as mechanical, electrical, and software engineers, especially when working across different time zones. Coordinating design reviews, troubleshooting issues, and aligning on project timelines can require extra effort in a virtual environment. Leveraging collaborative tools, setting regular check-ins, and documenting decisions thoroughly help ensure everyone stays aligned and project milestones are met efficiently.
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Machine Learning Systems Engineer

Machine Learning Systems Engineer

Motional

Las Vegas, NV • On-site, Remote

Other

Re-posted 6 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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