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Remote Machine Learning Jobs in Nevada (NOW HIRING)

Allegiant

Sr Engineer, Software I

Las Vegas, NV · On-site +1

$117K - $154.20K/yr

... learning.We develop travel and hospitality management applications for Airline, Hotel & Hospitality, Car and related products from online shopping, booking and logistics while supporting airline ...

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$26K

$43.4K

$89.6K

How much do remote machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for remote machine learning in Nevada is $43,363.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,100.00 and $46,800.00 per year, depending on experience, location, and employer.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Nevada? The most popular types of Machine Learning jobs in Nevada are:
What job categories do people searching Remote Machine Learning jobs in Nevada look for? The top searched job categories for Remote Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for Remote Machine Learning jobs? Cities in Nevada with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
OpenClaw AI Engineer (Remote)

OpenClaw AI Engineer (Remote)

Outlier AI

Las Vegas, NV • Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

About the Project

Outlier helps the world’s most innovative companies improve their AI agents by providing human feedback. Do you want to shape the future of autonomous agents like OpenClaw?

We collaborate with leading AI organizations to train Large Language Models (LLMs) to function as proactive, multi-step agents. Our projects focus on teaching these systems how to design, coordinate, and optimize complex, real-world architectural workflows.

Whether you are a passionate orchestration guru or experienced software developer — we want you to help us train the world's most advanced generative systems.

Ideal Qualifications

  • 2+ years of experience in backend engineering, AI automation, or complex systems integration.
  • Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting).
  • Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases.
  • Practical experience building for live, non-mocked environments and handling multi-turn system interactions.
  • Outstanding attention to detail and the ability to provide clear, high-density technical feedback on complex system behaviors.

Nice to have

  • Expertise building multi-stage coordination tasks where data acquisition leads to reasoned output.
  • Hands-on experience integrating agents with live tools such as Supabase, Gmail, and various APIs to solve real-world problems.
  • High level of comfort implementing persistent state and session discovery using MEMORY.md to track agent progress.
  • Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.

Apply