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Remote Full Stack Machine Learning Engineer Jobs in North Carolina

$110K - $140K/yr

The Machine Learning Engineer role is all about building, recruiting, management, internal communication and delivery - getting the product out the door, while ensuring the team is hitting their mark.

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

About the Role We are looking for a Full Stack Developer, with a heavier emphasis on front-end development, to produce scalable software solutions. You'll be part of a cross-functional team that ...

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Remote Full Stack Machine Learning Engineer information

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 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 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 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 the most commonly searched types of Full Stack Machine Learning Engineer jobs in North Carolina? The most popular types of Full Stack Machine Learning Engineer jobs in North Carolina are:
What are popular job titles related to Remote Full Stack Machine Learning Engineer jobs in North Carolina? For Remote Full Stack Machine Learning Engineer jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in North Carolina look for? The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in North Carolina are:
What cities in North Carolina are hiring for Remote Full Stack Machine Learning Engineer jobs? Cities in North Carolina with the most Remote Full Stack Machine Learning Engineer job openings:
Infographic showing various Remote Full Stack Machine Learning Engineer job openings in North Carolina as of June 2026, with employment types broken down into 84% Full Time, 8% Part Time, and 8% Contract. Highlights an 42% Physical, 2% Hybrid, and 56% Remote job distribution.
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Sunergi Inc

Remote

$110K - $140K/yr

Full-time

Posted 29 days ago


Job description

Sunergi Inc.Machine Learning EngineerFull-time


We are expanding rapidly and are seeking new, experienced and hands-on team members who think outside of the box (and are not afraid to share their thoughts), will deliver unique ideas and like to work in a fast-paced environment on cutting edge projects.


Our missionWe aim to map the best plots for solar panels in the United States.



The Machine Learning Engineer role is all about building, recruiting, management, internal communication and delivery - getting the product out the door, while ensuring the team is hitting their mark. Furthermore, the role will help to grow the engineering team, establish the engineering culture and remove impediments to help team members be able to provide their best.
Key Qualifications
  • You are a core contributor on ML projects with a focus on data ingestion, transformation and presentation for ML apps and reporting.
  • Passionate and dedicated track record of designing and implementing scalable, performant data pipelines, data services, and data products.
  • This is a hands-on position, expect to write more code.
  • Proficiency in at least one programming language (Java, Python or Scala) and a tried understanding of SQL.
  • Previous experience of dealing with multivariate data at petabyte scale, especially in the time-series domain.
  • Be able to communicate collaboratively with Data Scientists and ML Software developers to understand requirements we have and deliver best in class data platform.
  • Previous experience with statistical modeling and deep learning frameworks / libraries we use is required.
  • Strong aptitude for learning new technologies related to Data Management and Data Science.
  • Proven record to create and perform independently and within a fast-paced, team-oriented environment.
  • Work with structured and unstructured data. Perform data cleansing, scraping unstructured data and converting into structured data.
  • Evaluate, benchmark and improve the scalability, robustness, efficiency and performance of big data platform and applications.
  • Experience with Kubernetes, Docker is a plus
Description

In this role, handle implementing data pipelines focused on Machine Learning applications. 


  • You will develop data sets for POCs to demonstrate new insights. 
  • Several of these may lead to fully operational ML models and deploy and own the life-cycle on in-house and third party cloud environments. 
  • You will partner with various cross functional teams to define, develop and implement data technology solutions, with an emphasis on providing superior foundational data for ML applications. 
  • A strong understanding of distributed data systems and experience in using open source frameworks to build applications is required. 
  • A solid understanding of Deep learning platforms such as Keras, Tensor-flow and/or PyTorch is highly desirable, as is an ability to deploy solutions based on these platforms. 
  • Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads, and working with partner teams to ensure scalability, business continuity and appropriate turnaround time is a key part of the operationalization effort. 
  • As a member of the team, you will be expected to take ownership of individual platform components and help set the vision and architecture for those. 
  • In the process, you will identify the requirements of new features, and propose design and drive the solution. 
  • A strong understanding of data governance and data privacy is expected for this role in keeping with Apple's strong commitment to the same.
Education & Experience

B.S or M.S in Computer Science, Mathematics, Statistics, Operational Research, Data Science / equivalent experience.

Additional Requirements
  • 3+ years of proven experience with Kubernetes, Docker is a plus

Compensation

  • 0.25% company equity, with vesting options up to 2%.
  • A strong, competitive salary upon reaching a seed round of funding. In the range of $110k-$140k/ year.



Employment Type: FULL_TIME