ZipRecruiter

Log In

2

Remote Full Stack Machine Learning Engineer Jobs in Delbarton, WV

QA Wolf

Customer Success Manager

Canada, KY · Remote

$164.40K - $246.60K/yr

Remote in US, UK, or Canada* We are looking for someone who: * Has 3+ years of experience as a ... Collaborate with sales, product, and engineering to share feedback and improve the customer ...

Juniper Square

Senior Product Manager, Private Credit

Canada, KY · On-site +1

$118.80K - $156.80K/yr

Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience ... engineering teams * Ability to operate effectively across the full SDLC-from discovery through ...

Juniper Square

Senior Data Product Services Manager

Canada, KY · On-site +1

$118.80K - $156.80K/yr

Our mission at Juniper Square is to unlock their full potential. We're the Operations Partner ... Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience ...

People also search for

All JobsRemote Full Stack Machine Learning Engineer JobsRemote Full Stack Machine Learning Engineer Jobs in Delbarton, WV

Remote Full Stack Machine Learning Engineer information

See Delbarton, WV salary details

$42.2K

$127.9K

$180.8K

How much do remote full stack machine learning engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for remote full stack machine learning engineer in Delbarton, WV is $127,888.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,300.00 and $149,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.

What are some common challenges faced by remote Full Stack Machine Learning Engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

What is a Remote Full Stack Machine Learning Engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

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

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

What cities near Delbarton, WV are hiring for Remote Full Stack Machine Learning Engineer jobs? Cities near Delbarton, WV with the most Remote Full Stack Machine Learning Engineer job openings:
Remote Full Stack Machine Learning Engineer jobs near you
Customer Success Manager

Customer Success Manager

QA Wolf

Canada, KY • Remote

$164.40K - $246.60K/yr

Full-time

Medical, Dental, Vision, PTO

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

Job description

We're on a mission to eliminate every software bug in the world. Companies spend over $70 billion a year on software testing...with not-so-great results. Bugs continue to wreak havoc on customers and prevent companies from achieving their goals.
QA Wolf is the first QA solution that guarantees automated test coverage. We help world-class teams ship faster and more confidently and are the top rated QA solution on G2.
QA Wolf is backed by top-tier venture capital and industry leaders including Scale, Inspired Capital, and founders of PayPal and AngelList. The founding leadership team brings experience from Amazon, Bridgewater, ZipDrug, and more.
QA Wolf is headquartered in Seattle and is a remote-first team. We are looking for a strategic, revenue-owning Customer Success Manager (CSM) to join our team.
Location: Remote in US, UK, or Canada*
We are looking for someone who:

  • Has 3+ years of experience as a Customer Success Manager or Account Executive managing full-lifecycle relationships in a technical SaaS environment with multiple stakeholders
  • Has proven success carrying a quota for renewals and/or expansions, with a strong track record of driving retention and growth
  • Is skilled at engaging VP- and C-level stakeholders, particularly in Product, Engineering, and QA
  • Thrives in early-stage startups where adaptability, ownership, and initiative are key
  • Thinks strategically and connects product value to customer business outcomes
  • Shares our values
Things you will do:
  • Manage a portfolio of 20-25 customers across onboarding, adoption, renewal, and expansion
  • Understand customer goals and workflows to drive outcomes and long-term value
  • Serve as a trusted advisor on QA and automated testing best practices
  • Create and execute success plans that clearly link product usage to business impact
  • Build and maintain alignment with technical and executive stakeholders
  • Identify risks early, handle objections, and manage escalations with clarity and urgency
  • Collaborate with sales, product, and engineering to share feedback and improve the customer experience
  • Own forecasting, renewals, and expansion opportunities across your accounts
  • Deliver against targets for Net and Gross Dollar Retention (NDR/GDR)
We offer great compensation and many other benefits including:
  • Compensation
    • USD: $100K-$140K base | $120K-$180K OTE
    • CAD: $137K-$191.8K base | $164.4K-$246.6K OTE
    • GBP: £78K-£109.2K base | £93.6K-£140.4K OTE
  • 100% Medical, dental, and vision
  • 28 days of personal time off (PTO)
  • A remote-first culture allows you to work virtually anywhere
Don't have the required experience? We've found some of our best candidates come from non-traditional sources. If this is you, feel free to email csmhiring@qawolf.com with why you think you would be a great fit. Depending on your background, you may join the team as either Customer Success Associate or a Customer Success Manager.
Our Values
Make magic. We want to build a magical product for our customers and magical place to work. Magic is striving for better than the best. Working with exceptional colleagues is exciting, inspiring, and the most important factor for creating a magical place to work.
Be open. Being open provides context people need to make great decisions. Openness builds trust, showing progress creates momentum, and open learnings from failures help us get better.
Have freedom and ownership. Giving people freedom instead of developing processes to prevent them from using their own judgement, creates better decision making and accountability. To give people freedom they must have the skills, context, and ownership mentality to solve problems self-directed.
Deliver impact fast. Creative mavericks are motivated by doing great work, not by being told what to do. By creating a magical environment to attract talented people, by being open and providing context to make great decisions, then we can provide freedom and ownership for people to do great work and deliver impact fast.
Learn more about our Mission and Values here.
Our Interview Process (Fast, Thoughtful, and Built for Builders ):
  • 30-minute intro with our Recruiting team - we'll align on experience, goals, and what excites you
  • Technical conversation with Customer Success Leadership - a deeper dive into your technical expertise and how you approach real-world CS challenges
  • Take-home challenge - show us how you build relationships, dive deep with customers, and drive outcomes
  • Take-home review with Leadership - a mock CS call and deeper discussion on what it would look like to join the team
  • Final chat with the Hiring Manager - ensuring strong alignment on expectations, impact, and long-term growth
  • Offer + welcome to the team
    Note: This is a fully remote position. However, all candidates must be physically located in and have legal authorization to work in the United States, Canada, or the United Kingdom, without the need for employer-sponsored work authorization, now or in the future. At this time, we are not sponsoring visas (e.g., H-1B, TN or E-3 in the United States) or supporting related work authorization.

Apply