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Machine Learning Teaching Assistant Jobs in Missouri

Jobgether

Design and implement advanced knowledge distillation pipelines, including teacher-student ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Varsity Tutors

Machine Learning Tutor

Columbia, MO · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Get matched with students best-suited to your teaching style and expertise. * Our AI-powered Tutor ...

Varsity Tutors

Machine Learning Tutor

Kansas City, MO · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Get matched with students best-suited to your teaching style and expertise. * Our AI-powered Tutor ...

Varsity Tutors

Machine Learning Tutor

Saint Louis, MO · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Get matched with students best-suited to your teaching style and expertise. * Our AI-powered Tutor ...

Archdiocese of St. Louis

Teaching Assistant

Saint Louis, MO · On-site

$13.50 - $17.25/hr

Supervise students during transitions, lunch, recess, and other school activities. * Assist students with assignments and reinforce learning concepts. * Communicate effectively with teachers and ...

Archdiocese of St. Louis

Teaching Assistant

Saint Louis, MO · On-site

$13.50 - $17.25/hr

Supervise students during transitions, lunch, recess, and other school activities. * Assist students with assignments and reinforce learning concepts. * Communicate effectively with teachers and ...

Archdiocese of St. Louis

Teaching Assistant

Saint Louis, MO · On-site

$13.50 - $17.25/hr

Supervise students during transitions, lunch, recess, and other school activities. * Assist students with assignments and reinforce learning concepts. * Communicate effectively with teachers and ...

Jobgether

Our partner is looking for a Machine Learning Engineer - Large Language Models based in Netherlands ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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Machine Learning Teaching Assistant information

How does a machine learning teaching assistant typically collaborate with professors and students during a course?

As a Machine Learning Teaching Assistant, you will work closely with professors to develop and grade assignments, clarify course concepts, and facilitate discussions in lectures or lab sessions. You often serve as a bridge between students and faculty, providing guidance on programming tasks, troubleshooting code, and offering feedback on projects. Regular office hours and online forums are common venues for this support, making strong communication skills and a solid grasp of machine learning fundamentals essential. This collaborative environment helps you deepen your expertise while supporting student learning.

What is a machine learning teaching assistant?

Machine Learning Teaching Assistants are individuals, often graduate students or knowledgeable undergraduates, who assist professors or instructors in teaching machine learning courses. Their responsibilities typically include helping students understand course material, grading assignments, holding office hours, and sometimes leading discussion or lab sessions. They act as a bridge between students and instructors, offering support for both theoretical concepts and practical implementation. By providing guidance and feedback, they help ensure students gain a solid understanding of machine learning principles and applications.

What are the key skills and qualifications needed to thrive as a machine learning teaching assistant, and why are they important?

To thrive as a Machine Learning Teaching Assistant, you need a solid foundation in machine learning concepts, programming (often Python), and relevant coursework or a degree in computer science or a related field. Familiarity with tools like Jupyter Notebooks, TensorFlow, PyTorch, and version control systems is commonly expected. Strong communication, patience, and organizational skills help you effectively support students and collaborate with instructors. These abilities ensure you can explain complex topics clearly, assist students efficiently, and contribute to a positive learning environment.
What are the most commonly searched types of Machine Learning Teaching jobs in Missouri? The most popular types of Machine Learning Teaching jobs in Missouri are:
What are popular job titles related to Machine Learning Teaching Assistant jobs in Missouri? For Machine Learning Teaching Assistant jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Machine Learning Teaching Assistant jobs in Missouri look for? The top searched job categories for Machine Learning Teaching Assistant jobs in Missouri are:
What cities in Missouri are hiring for Machine Learning Teaching Assistant jobs? Cities in Missouri with the most Machine Learning Teaching Assistant job openings:
Machine Learning Teaching Assistant jobs near you

Machine Learning Engineer - Distillation

Jobgether

On-site, Remote

Full-time

Posted 12 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer - Distillation based in Netherlands.

This role offers the opportunity to advance the efficiency and scalability of next-generation machine learning systems.
You will work at the intersection of research and production, transforming cutting-edge model optimization techniques into real-world solutions.
The position focuses on building smaller, faster, and more cost-effective AI models while maintaining high-quality performance.
You will design advanced distillation pipelines, run large-scale experiments, and contribute directly to production systems.
This is an opportunity for an ML engineer who enjoys deep technical challenges, experimentation, and practical innovation.
You will join a collaborative environment where your work directly influences model quality, performance, and product impact.

Accountabilities

As a Machine Learning Engineer focused on Distillation, you will design, develop, and optimize machine learning systems that improve model efficiency without compromising performance. You will combine research expertise with engineering execution to build scalable AI solutions.

  • Design and implement advanced knowledge distillation pipelines, including teacher-student approaches, self-distillation, and multi-teacher architectures.
  • Distill large foundation models into smaller, faster, and more efficient models optimized for production inference.
  • Run large-scale machine learning experiments to evaluate model quality, latency, efficiency, and cost tradeoffs.
  • Analyze experimental results and use insights to improve model performance and optimization strategies.
  • Collaborate with research teams to transform emerging distillation techniques into reliable production-ready implementations.
  • Optimize training and inference performance, including memory usage, throughput, latency, and computational efficiency.
  • Develop and improve internal tools, evaluation frameworks, and experiment tracking systems.
  • Contribute to improving machine learning workflows and engineering best practices.
  • Explore opportunities to contribute to open-source models, research initiatives, or technical tooling.
Requirements

The ideal candidate is a machine learning engineer with strong experience in deep learning, model optimization, and production-oriented AI development. You should have hands-on experience with distillation techniques and the ability to balance research innovation with practical engineering delivery.

  • Strong background in machine learning, deep learning, and neural network architectures.
  • Hands-on experience implementing model distillation techniques for large language models or other neural networks.
  • Solid understanding of training dynamics, optimization methods, loss functions, and model evaluation.
  • Experience working with PyTorch, JAX, or similar modern machine learning frameworks.
  • Experience running experiments in multi-GPU or distributed training environments.
  • Ability to evaluate and optimize tradeoffs between model quality, performance, latency, and cost.
  • Strong programming and software engineering skills with the ability to build production-ready ML systems.
  • Practical mindset focused on shipping impactful solutions rather than only theoretical research.
  • Experience with inference optimization techniques such as quantization, pruning, or kernel optimization is a plus.
  • Familiarity with language model evaluation methodologies is preferred.
  • Open-source contributions, research publications, or experience in fast-moving startup environments are considered valuable.
Benefits
  • Competitive compensation package with meaningful equity opportunities.
  • Opportunity to work on core machine learning systems that directly impact product performance and efficiency.
  • High ownership role with significant influence over technical direction and roadmap.
  • Collaboration with a small, senior team combining research expertise and engineering excellence.
  • Remote-friendly work environment with an async-first culture.
  • Opportunity to solve challenging AI optimization problems at scale.
  • Ability to contribute to advanced model development and emerging AI technologies.
  • Fast-paced environment that encourages innovation, experimentation, and technical growth.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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