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Remote Spacex Machine Learning 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 ...

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 ...

Motional

Senior Embedded Software Engineer

Las Vegas, NV · On-site +1

$149K - $198K/yr

Experience deploying Machine Learning models. * Experience working with GPUs. * Experience working ... be fully remote. The salary range for this role is an estimate based on a wide range of ...

Relativity

Principal Applied Scientist

Las Vegas, NV · On-site +1

$134K - $202K/yr

Posting Type Remote/Hybrid Job Overview At Relativity, we build technology that helps people ... Required Skills Algorithms, Data Analysis, Machine Learning (ML), Natural Language, Python ...

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Remote Spacex Machine Learning information

What does a Remote SpaceX Machine Learning Engineer do?

A Remote SpaceX Machine Learning Engineer uses data-driven algorithms and models to solve complex problems for SpaceX, often focusing on areas such as rocket manufacturing, satellite communications, and mission planning. Working remotely, these engineers collaborate with cross-functional teams to design, develop, and implement machine learning solutions that improve efficiency, safety, and performance. They may analyze large datasets, build predictive models, and deploy AI systems to support SpaceX's ambitious goals in space exploration.

What are some unique challenges of working remotely as a Machine Learning Engineer at SpaceX, and how can candidates prepare for them?

Working remotely as a Machine Learning Engineer at SpaceX presents unique challenges such as collaborating across distributed teams, managing time zones, and maintaining effective communication with colleagues involved in hardware and aerospace projects. To succeed, candidates should be proactive in seeking regular updates, use collaborative tools efficiently, and be comfortable working independently while still aligning with team objectives. Familiarity with remote development environments and a strong ability to document and present complex models are also key to thriving in this role.

What is the difference between Remote Spacex Machine Learning vs Remote Spacex Data Scientist?

AspectRemote Spacex Machine LearningRemote Spacex Data Scientist
Required CredentialsAdvanced degree in Computer Science, AI, or related field; experience in ML frameworksDegree in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, algorithms, and AI systems for space applicationsAnalyzing data, creating insights, and supporting decision-making processes
Employer & Industry UsageUsed in AI-driven space missions, autonomous systems, and roboticsApplied in data analysis, reporting, and predictive modeling for space projects

Remote Spacex Machine Learning specialists focus on developing AI models for space technology, while Data Scientists analyze data to inform decisions. Both roles require strong technical skills and often collaborate but serve different core functions within the industry.

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

To excel as a Remote SpaceX Machine Learning Engineer, you need strong expertise in machine learning, data analysis, and programming languages like Python, along with a relevant degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud computing platforms, and version control systems is typically necessary, and certifications in machine learning or data science can be advantageous. Excellent problem-solving skills, strong communication, and the ability to collaborate remotely are key soft skills that help you stand out. These skills ensure you can develop robust ML models that support SpaceX’s technical goals while effectively working within distributed teams.
What are the most commonly searched types of Spacex Machine Learning jobs in Nevada? The most popular types of Spacex Machine Learning jobs in Nevada are:
What are popular job titles related to Remote Spacex Machine Learning jobs in Nevada? For Remote Spacex Machine Learning jobs in Nevada, the most frequently searched job titles are:
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What cities in Nevada are hiring for Remote Spacex Machine Learning jobs? Cities in Nevada with the most Remote Spacex Machine Learning job openings:
Remote Spacex Machine Learning jobs near you
Machine Learning Systems Engineer

Machine Learning Systems Engineer

Motional

Las Vegas, NV • On-site, Remote

Other

Re-posted 2 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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