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Remote Full Stack Machine Learning Engineer Jobs in New Jersey

QCi

Job Title: Software Engineer, Full Stack Location: Remote Division: Technology Department ... quantum machines to the world today. We are the pioneers of Entropy Quantum Computing (EQC ...

Diverse Lynx

AI/ML Engineer

Secaucus, NJ · Remote

... Machine Learning. * Work extensively with Large Language Models (LLMs) to build and refine AI ... Engage in full-stack development, with a focus on Python for backend services and React for ...

Eliassen Group

Full Stack Engineer

Jersey City, NJ · On-site +1

$85 - $89/hr

Full Stack Engineer 1 Pershing Plaza, NJ Type: Contract Category: Development Industry: Financial Services Reference ID: JN -052026-107023 Date Posted: 06/17/2026 Shortcut: * Description

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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 New Jersey? The most popular types of Full Stack Machine Learning Engineer jobs in New Jersey are:
What are popular job titles related to Remote Full Stack Machine Learning Engineer jobs in New Jersey? For Remote Full Stack Machine Learning Engineer jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in New Jersey look for? The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in New Jersey are:
What cities in New Jersey are hiring for Remote Full Stack Machine Learning Engineer jobs? Cities in New Jersey with the most Remote Full Stack Machine Learning Engineer job openings:
Remote Full Stack Machine Learning Engineer jobs near you

Remote Machine Learning Engineer

Angenex

Jersey City, NJ • Remote

Other

Posted 26 days ago

Job description

Remote Machine Learning Engineer

Jersey City, NJ, United States

About the Job

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.

Responsibilities

- Build and deploy the ML pipelines that power the company machine learning platform.

- Manage MLOps infrastructure to monitor and optimize models.

Qualifications

Experience:

1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Proficiency across topics in machine learning and statistics.

Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.

Familiarity with CNNs, RNN, LSTMs, and the latest research trends.

Experience implementing, deploying, and maintaining production machine learning systems.

Experience monitoring and optimizing model performance.

Experience with Linux, Docker and AWS, and basic development operations.

Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

Apply