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Freelance Google Machine Learning Engineer Jobs in Nevada

Senior Machine Learning Engineer

Las Vegas, NV · On-site +1

$117K - $154K/yr

About the Role We're looking for a Senior Machine Learning Engineer to join our team during an exciting phase of growth. In this role, you'll be responsible for building and operating the core ...

Senior Machine Learning Engineer

Las Vegas, NV · On-site

$117K - $154K/yr

About the Role We're looking for a Senior Machine Learning Engineer to join our team during an exciting phase of growth. In this role, you'll be responsible for building and operating the core ...

AI Architect

Las Vegas, NV · On-site

$60.25 - $79.25/hr

Required Skills and Experience Proven experience as an AI Architect, Machine Learning Engineer, or similar role focused on Agentic AI or Autonomous Systems.Vertex AI BigQuery Cloud Functions Google ...

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 ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Reno, NV · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Freelance Google Machine Learning Engineer information

What does a freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Nevada?

For Freelance Google Machine Learning Engineer jobs in Nevada, the most frequently searched job titles are:

What cities in Nevada are hiring for Freelance Google Machine Learning Engineer jobs?

Cities in Nevada with the most Freelance Google Machine Learning Engineer job openings:

Senior Machine Learning Engineer

Las Vegas, NV • On-site, Remote

$117K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Job description

About TensorWave
Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.
About the Role
We're looking for a Senior Machine Learning Engineer to join our team during an exciting phase of growth. In this role, you'll be responsible for building and operating the core systems that power large-scale ML training and inference across TensorWave's GPU platform, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.
What You'll Do
  • Design, operate, and improve ML infrastructure systems supporting distributed training and inference workloads
  • Build reliable, repeatable workload execution and orchestration patterns across shared GPU environments
  • Troubleshoot performance, reliability, and scalability issues across the ML stack
  • Partner with ML, systems, and platform teams to improve developer experience and operational efficiency

Who You Are
Required Qualifications
  • Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
  • Expertise supporting production ML systems using SLURM and Kubernetes
  • Strong understanding of GPU-accelerated workloads and distributed systems concepts
  • Solid Linux fundamentals and experience debugging infrastructure-level issues
  • Ability to build automation and tooling - Python, Go, etc.

Preferred Qualifications
  • Experience working across schedulers, orchestration platforms, or cluster managers
  • Familiarity with large-scale GPU environments or HPC-style systems
  • Experience improving infrastructure reliability, utilization, or performance at scale

What We Offer
  • Stock Options
  • 100% paid Medical, Dental, and Vision insurance for Employees
  • Company Health Savings Account Contributions
  • 100% paid Short Term and Long Term Disability Insurance for Employees
  • Life and Voluntary Supplemental Insurance Options
  • Other Insurance Options, such as Pet & Legal Insurance
  • Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support
  • Flexible Spending Account
  • 401(k)
  • Employee Assistance Program
  • Flexible PTO
  • Paid Holidays
  • Parental Leave
  • Other In-Office Perks

Equal Employment Opportunity
TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.
Reasonable Accommodations
TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.
Employment Eligibility
All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.
Background Checks
Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.
Data Privacy Notice
By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.