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Remote Machine Learning Jobs in Nevada (NOW HIRING)

We operate at the intersection of machine learning, programmatic media, and full-funnel mobile ... Remote-first with real flexibility. Work from anywhere in the US, on a schedule that respects your ...

We operate at the intersection of machine learning, programmatic media, and full-funnel mobile ... Remote-first with real flexibility. Work from anywhere in the US, on a schedule that respects your ...

About the Role Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate decisions. Our mission is ...

This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...

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Remote Machine Learning information

See Nevada salary details

$26K

$43.4K

$89.6K

How much do remote machine learning jobs pay per year?

As of Jul 11, 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 engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

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 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.

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 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.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
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 cities in Nevada are hiring for Remote Machine Learning jobs? Cities in Nevada with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Nevada as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $43,363 per year, or $20.8 per hour.

Senior Recruiter

RZR Global Inc.

Las Vegas, NV • Remote

Other

Posted 15 days ago


Job description

Who Are We?

RZR is an AI-native advertising platform built for the next era of performance marketing. We operate at the intersection of machine learning, programmatic media, and full-funnel mobile growth, powering campaigns for some of the world's most ambitious advertisers. Our platform is purpose-built to deliver outcomes at scale, not just impressions.

We are a team of builders, operators, and technologists who believe the advertising industry is overdue for a fundamental rethink. We move fast, operate with a high degree of ownership, and hold ourselves to an exceptionally high standard of craft.

RZR is scaling aggressively with an active M&A pipeline and a platform vision that puts us on a path to becoming an industry leader. This is a rare opportunity to join a company at an inflection point and help shape what it becomes.

Role Overview

RZR is hiring a Senior Recruiter to own US & EMEA hiring across all functions as we scale. This is not a reactive, post-and-pray role. You'll carry an active portfolio of roles spanning Engineering, GTM, and G&A, build pipelines from scratch where inbound falls short, and operate as a true partner to hiring managers across the business.

You'll report directly to the Global Head of Talent Acquisition, with no layers between you and the decision-maker. Your work will be visible, your perspective will be heard, and your results will directly shape how RZR builds its team over the next critical phase of growth.

This is the right role for a recruiter who is done being a coordinator and wants to operate at the full strategic and executional level of the craft.

Key Responsibilities
  • Own the end-to-end recruiting process for an active portfolio of 10-15 US roles across Engineering, GTM, and G&A, from kick-off call through offer acceptance.
  • Build proactive sourcing strategies for every role, constructing pipelines from scratch where inbound is insufficient, using LinkedIn Recruiter, Boolean search, and creative outreach.
  • Partner closely with hiring managers to define role requirements, calibrate quickly on candidate quality, and maintain aligned expectations throughout the search.
  • Deliver an exceptional candidate experience at every stage: timely communication, clear and honest feedback, and a process that candidates want to tell others about.
  • Keep pipeline data clean and current in the ATS so the team always has an accurate picture of where things stand.
  • Drive offers through to close, navigating competing offers and managing candidate expectations with confidence and care.
  • Assist in weekly and monthly business review reportings. Collecting data, ensuring accuracy, and making recommendations for improvement upon analysis. 
  • Actively contribute to how the TA team operates, flagging friction points and pushing for smarter processes over time.
Required Skills and Experience
  • 4+ years of full-cycle in-house recruiting experience, or agency experience with a significant in-house component.
  • Proven ability to recruit across multiple functions simultaneously without dropping quality or candidate experience.
  • Strong independent sourcing skills: you can build a pipeline from zero, not just manage inbound.
  • Experience with Greenhouse or a comparable enterprise ATS.
  • Comfortable moving fast with shifting priorities and limited playbooks.
  • Based in the US with availability during core US business hours.
  • Nice to have: experience in high-growth tech, adtech, or gaming; familiarity with US hiring compliance (EEOC, offer letter standards); exposure to globally distributed TA teams; ability to use pipeline data to influence hiring manager behavior.
Why Join RZR?
  • Direct access, real influence. You'll work hand-in-hand with the Global Head of TA with no layers in between. Your work is seen. Your perspective shapes how the team operates.
  • Scope across the whole business. You won't be siloed into one function. Engineering, GTM, G&A: you'll recruit across all of it and build real business depth at RZR.
  • The timing is right. US headcount is scaling now. The recruiter who joins at this moment will have a lasting impact on the people and culture we build; that opportunity doesn't come around often.
  • A team that does this right. You'll be part of a global TA org with real infrastructure, a disciplined hiring process, and colleagues who care about quality as much as speed.
  • Remote-first with real flexibility. Work from anywhere in the US, on a schedule that respects your time zone.
RZR Behaviors

RZR operates by eight core behaviors: Extreme Ownership Move Fast Drive for Excellence Proactive Communication Courage Curiosity Deliver Results Manage Ambiguity