2

Part Time Machine Learning Software Engineer Jobs in New Jersey

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 ...

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 ...

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 ...

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 ...

next page

Showing results 1-20

Part Time Machine Learning Software Engineer information

What are the key skills and qualifications needed to thrive as a Part Time Machine Learning Software Engineer, and why are they important?

To thrive as a Part Time Machine Learning Software Engineer, you need strong programming skills in languages like Python, a solid understanding of machine learning concepts, and relevant experience or a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems is typically required. Excellent problem-solving abilities, time management, and clear communication are essential soft skills, especially when working independently or with remote teams. These skills ensure you can efficiently develop, implement, and maintain machine learning solutions while collaborating effectively on a flexible schedule.

How does working part-time as a Machine Learning Software Engineer impact collaboration with full-time team members?

As a part-time Machine Learning Software Engineer, you may encounter unique challenges in staying aligned with full-time colleagues, especially when working on fast-paced or iterative projects. Effective communication, clear documentation, and regular check-ins are essential to ensure seamless collaboration and project continuity. Many teams use asynchronous tools and flexible stand-up meetings to accommodate varying schedules, allowing part-time engineers to contribute meaningfully without missing critical updates. Proactively engaging with teammates and being transparent about your availability are key to maintaining strong collaborations and delivering successful outcomes.

What does a Part Time Machine Learning Software Engineer do?

A Part Time Machine Learning Software Engineer develops and deploys machine learning models and algorithms on a flexible, part-time schedule. They work on tasks such as data preprocessing, feature engineering, model training, and evaluation, often contributing to software projects that incorporate AI solutions. These engineers collaborate with teams to integrate machine learning models into applications, ensuring efficiency and accuracy, while balancing their workload within limited hours. Their role is ideal for those seeking flexible work arrangements in the rapidly evolving field of artificial intelligence.

What is the difference between Part Time Machine Learning Software Engineer vs Data Scientist?

AspectPart Time Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops ML models, algorithms, and software solutions; often collaborates with engineering teamsAnalyzes data, builds models, interprets results; may work in research or business teams
Industry UsageUsed in tech companies, startups, and industries applying ML solutionsCommon in finance, healthcare, marketing, and research sectors

While both roles involve working with data and algorithms, a Part Time Machine Learning Software Engineer primarily focuses on developing and deploying ML models within software applications, often in a part-time capacity. A Data Scientist emphasizes data analysis, interpretation, and modeling to inform business decisions. The roles overlap in skills and tools but differ in their core focus and responsibilities.

What are the most commonly searched types of Machine Learning Software Engineer jobs in New Jersey? The most popular types of Machine Learning Software Engineer jobs in New Jersey are:
Machine Learning Tutor

Machine Learning Tutor

Varsity Tutors

Paramus, NJ • Remote

$40/hr

Part-time

Posted 25 days ago


Varsity Tutors rating

5.7

Company rating: 5.7 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

13th of 21 rated private schools and tutoring


Job description

About the Job
The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the flexibility to set your own schedule, earn competitive rates, and make a real impact on students' academic success and understanding. All from the comfort of your home.
Why Join Our Platform?
  • Earn incrementally higher pay for each session with the same student, reaching up to $40/hour.
  • Get paid up to twice per week, ensuring fast and reliable compensation for the tutoring sessions you conduct and invoice.
  • Set your own hours and tutor as much as you'd like.
  • Tutor remotely using our purpose-built Live Learning Platform. No commuting required.
  • Get matched with students best-suited to your teaching style and expertise.
  • Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson generation, and engagement features, helping you save prep time and focus on impactful teaching.
  • We handle the logistics—you just invoice for your tutoring sessions, and we take care of payments.

What We Look For In a Machine Learning Tutor
  • Advanced Subject Mastery: Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science roles and advanced AI coursework.
  • Conceptual Teaching & Problem-Solving: Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric interpretation. Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ROC curves. Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics.
  • Curriculum Awareness & Adaptive Instruction: Familiar with machine learning curricula and common challenges such as understanding bias-variance tradeoff, selecting appropriate algorithms for problem types, and interpreting model performance beyond accuracy. Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to support students from introductory statistics-based ML through advanced deep learning and deployment.
  • Effective Teaching Methods: Ability to identify concepts students commonly struggle with, explain material using multiple approaches, and adapt instruction to meet individual learning needs and styles.
  • Strong communication skills and a friendly, engaging teaching style.
  • Ability to adapt to different learning styles and student needs.

Ways To Connect With Students
  • 1-on-1 Online Tutoring - Provide personalized instruction to individual students.
  • Instant Tutoring - Accept on-demand tutoring requests whenever you're available.

About Varsity Tutors And 1-on-1 Online Tutoring
Our mission is to transform the way people learn by leveraging advanced technology, AI, and the latest in learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students receive customized instruction that helps them achieve their learning goals. Our platform is designed to match students with the right tutors, fostering better outcomes and a passion for learning.
Please note: Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West Virginia or Puerto Rico.

What Varsity Tutors employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom