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Machine Learning Engineer Jobs in Charlottesville, VA

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

Perform data cleaning, feature engineering, and exploratory data analysis (EDA). * Apply advanced statistical methods and machine learning techniques to solve complex analytical problems. * Support ...

Perform data cleaning, feature engineering, and exploratory data analysis (EDA). * Apply advanced statistical methods and machine learning techniques to solve complex analytical problems. * Support ...

Perform data cleaning, feature engineering, and exploratory data analysis (EDA). * Apply advanced statistical methods and machine learning techniques to solve complex analytical problems. * Support ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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Machine Learning Engineer information

See Charlottesville, VA salary details

$31.3K

$127.7K

$192K

How much do machine learning engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for machine learning engineer in Charlottesville, VA is $127,747.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,700.00 and $153,800.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Charlottesville, VA? The most popular types of Machine Learning Engineer jobs in Charlottesville, VA are:
What are popular job titles related to Machine Learning Engineer jobs in Charlottesville, VA? For Machine Learning Engineer jobs in Charlottesville, VA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Charlottesville, VA look for? The top searched job categories for Machine Learning Engineer jobs in Charlottesville, VA are:
What cities near Charlottesville, VA are hiring for Machine Learning Engineer jobs? Cities near Charlottesville, VA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Charlottesville, VA as of June 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $127,747 per year, or $61.4 per hour.
Machine Learning Tutor

Machine Learning Tutor

Varsity Tutors

Charlottesville, VA • Remote

$40/hr

Part-time

Posted 6 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.

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