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Remote Learning Enablement Jobs in Nevada (NOW HIRING)

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Remote Learning Enablement information

What are the key skills and qualifications needed to thrive in remote learning enablement, and why are they important?

To thrive in Remote Learning Enablement, you need expertise in instructional design, digital pedagogy, and a solid understanding of e-learning best practices, often supported by a degree in education or instructional technology. Familiarity with Learning Management Systems (LMS) like Canvas or Moodle, authoring tools such as Articulate Storyline, and relevant certifications (e.g., Certified Professional in Learning and Performance) are highly valuable. Strong communication, problem-solving, and adaptability enable effective collaboration and support for diverse learners and educators in virtual environments. These competencies are essential to create engaging, accessible, and impactful remote learning experiences that drive learner success.

What are some common challenges faced by professionals in remote learning enablement, and how can they be addressed?

Professionals in Remote Learning Enablement often encounter challenges such as maintaining learner engagement, ensuring smooth technology adoption, and supporting diverse learning needs across distributed teams. Overcoming these challenges involves leveraging interactive tools, providing clear onboarding for digital platforms, and fostering open communication with both instructors and learners. Collaborating closely with IT, instructional designers, and organizational leaders helps to continuously improve the remote learning experience and resolve issues promptly.

What is remote learning enablement?

Remote Learning Enablement refers to the strategies, tools, and support systems that help individuals or organizations successfully conduct learning activities outside of traditional, in-person settings. This can involve the use of technology platforms, digital resources, instructional design, and ongoing technical support to ensure learners have access to quality education from any location. Professionals in this field often work to implement best practices, train educators, and troubleshoot issues to create effective and engaging remote learning experiences.

What is the difference between Remote Learning Enablement vs Instructional Designer?

AspectRemote Learning EnablementInstructional Designer
CredentialsTypically requires education or training in education, e-learning, or related fieldsUsually holds degrees in education, instructional design, or related disciplines
Work EnvironmentPrimarily remote, supporting online learning platforms and toolsOften remote or hybrid, designing and developing educational content
Employer & IndustryEducational institutions, corporate training, e-learning companiesEducational institutions, corporate training, e-learning firms
Primary FocusEnabling effective online learning experiences through support and technologyCreating and designing instructional materials and curricula

Remote Learning Enablement focuses on supporting and facilitating online education through technology and support roles, while Instructional Designers primarily develop and design educational content and curricula. Both roles often work remotely and serve similar industries, but their core responsibilities differ in focus and skill set.

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

Software Engineer, ML Dev Enablement

Motional

Las Vegas, NV • On-site, Remote

Other

Re-posted 5 days ago

Job description

Mission Summary:

We are looking for a Software Engineer to join our ML Infrastructure: Dev Enablement Team. Our mission is to build a frictionless development environment that empowers our researchers and engineers to rapidly innovate on deep learning models for autonomous driving.

We manage a high-scale Cloud Development Environment (CDE) platform that provides standardized, high-performance workspaces for ML development. As we evolve, in this role, you'll spearhead high-impact initiatives: designing multi-cloud setups to maximize GPU availability, driving deep-level model optimization, and building next-generation Agentic AI toolings. You will play a pivotal role in ensuring our training ecosystem remains cutting-edge, resilient and highly efficient.

What You'll Be Doing:

  • Build Agentic AI Tooling: Design, develop, and enhance Agentic AI tools and systems to automate workflows, streamline the ML lifecycle, and empower developer productivity.
  • Scale Core Infrastructure: Drive the continuous development of our core ML infrastructure and existing CDE platform, leveraging Kubernetes to build robust, high-scale distributed solutions.
  • System-Level ML Optimization: Partner closely with ML Researchers to profile and optimize distributed training jobs (PyTorch/DDP) and data pipelines. Focus on resolving system-level bottlenecks-such as data loading (I/O), memory management, and network communication overhead-to maximize GPU utilization and training throughput.
  • Collaborate Cross-Functionally: Partner with ML engineers and data scientists to understand their complex needs, bridging the gap between underlying infrastructure and model development.

What We're Looking For:

  • BS or MS in Computer Science or related field
  • Strong knowledge of software engineering principles and distributed systems.
  • Strong proficiency with Python or Go or C++
  • Experience with building on AWS services or other Cloud platforms and container orchestration using Kubernetes.
  • Experience with the various stages of the ML development lifecycle
Bonus Points:
  • Hands-on experience with ML model profiling and performance optimization for distributed training.
  • Experience managing or working with high-performance compute resources (GPUs).
  • Experience with ML frameworks such as PyTorch or Ray.
  • Experience building, integrating, or enhancing Agentic AI systems and LLM-driven developer tools.

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

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