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Junior Machine Learning Compiler Engineer Jobs in Radford, VA

Python Tutor

Blacksburg, VA · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Contribute to engineering projects focused on developing computer vision measurement systems incorporating machine learning and AI technologies. * Collaborate with cross-functional teams to design ...

Contribute to engineering projects focused on developing computer vision measurement systems incorporating machine learning and AI technologies. * Collaborate with cross-functional teams to design ...

Contribute to engineering projects focused on developing computer vision measurement systems incorporating machine learning and AI technologies. * Collaborate with cross-functional teams to design ...

Civil Design Engineer

Radford, VA · On-site

$63K - $79K/yr

Are you an aspiring or junior engineer looking to build a versatile foundation in civil design ... We invest in your continuous learning, offering path-to-licensure guidance, professional ...

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

College of Engineering Department: Chemical Engineering Location: Blacksburg, Virginia Categories ... in AI and machine learning. The post-doctoral associate will also be responsible for data ...

Showing results 41-60

Junior Machine Learning Compiler Engineer information

See Radford, VA salary details

$31.8K

$68.2K

$104K

How much do junior machine learning compiler engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for junior machine learning compiler engineer in Radford, VA is $68,202.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,100.00 and $76,000.00 per year, depending on experience, location, and employer.

What does a junior machine learning compiler engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are typical projects and responsibilities for a junior machine learning compiler engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

What are the key skills and qualifications needed to thrive as a junior machine learning compiler engineer, and why are they important?

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

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

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Radford, VA?

The most popular types of Machine Learning Compiler Engineer jobs in Radford, VA are:

What cities near Radford, VA are hiring for Junior Machine Learning Compiler Engineer jobs?

Cities near Radford, VA with the most Junior Machine Learning Compiler Engineer job openings:

Infographic showing various Junior Machine Learning Compiler Engineer job openings in Radford, VA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $68,202 per year, or $32.8 per hour.

Python Tutor

Varsity Tutors

Blacksburg, VA • Remote

$18 - $40/hr

Part-time

Re-posted 4 days ago


Varsity Tutors rating

5.9

Company rating: 5.9 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

12th of 24 rated private schools and tutoring


Job description

About the Job
The Varsity Tutors Live Learning Platform has thousands of students looking for online Python 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 Python Tutor
  • Advanced Subject Mastery: Deep knowledge of Python syntax, data types, control flow, functions, object-oriented programming, file handling, modules and packages, list comprehensions, error handling, and popular libraries including NumPy, Pandas, and Matplotlib. Ability to explain Pythonic programming conventions, decorators, and generators while preparing students for data science, web development, automation, and computer science coursework.
  • Conceptual Teaching & Problem-Solving: Skilled at breaking down algorithm design, data manipulation, and object-oriented programming concepts in Python. Guides students through writing clean functions, manipulating data with Pandas, creating visualizations, implementing class hierarchies, and automating tasks with scripts. Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications.
  • Curriculum Awareness & Adaptive Instruction: Familiar with Python curricula at introductory through advanced levels and common challenges such as understanding indentation-based syntax, list versus dictionary selection, and debugging type errors. Adapts instruction using interactive notebooks, coding challenges, and project-based learning to support students from absolute beginners through advanced users preparing for data science, software development, or academic computing work.
  • 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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