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Machine Learning Teaching Assistant Jobs in North Carolina

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Machine Learning Teaching Assistant information

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.

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 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 North Carolina?

The most popular types of Machine Learning Teaching jobs in North Carolina are:

What are popular job titles related to Machine Learning Teaching Assistant jobs in North Carolina?

For Machine Learning Teaching Assistant jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Machine Learning Teaching Assistant jobs in North Carolina look for?

The top searched job categories for Machine Learning Teaching Assistant jobs in North Carolina are:

What cities in North Carolina are hiring for Machine Learning Teaching Assistant jobs?

Cities in North Carolina with the most Machine Learning Teaching Assistant job openings:

Infographic showing various Machine Learning Teaching Assistant job openings in North Carolina as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Sr. Machine Learning/AI Engineer

Financial Independence Group, LLC

Cornelius, NC โ€ข On-site

$96K - $132K/yr

Full-time

Re-posted 26 days ago


Job description

WHO WE ARE:

Financial Independence Group (FIG) is one of the nation's largest Finance and Insurance Marketing Organizations (FMO & IMO) in the country, partnering with thousands of financial professionals in all 50 states. FIG seeks to expand the availability of financial products and services to financial professionals and ultimately the clients and families they serve. This is accomplished through robust product offerings, innovative marketing, and cutting-edge technology.

Interested in learning more? Click here to find out what it's like to work at FIG.

ABOUT THE TEAM:

FIG's AI & Analytics Team is advancing the next generation of intelligent capabilities across the organization. We combine stateoftheart machine learning, modern data engineering, and agentdriven automation to enhance how FIG supports advisors, strengthens operations, and accelerates strategic decisionmaking.

We operate in a fastpaced, collaborative, and experimentationfriendly environment. Our team partners crossfunctionally with technology, operations, and business leaders to develop AI systems that deliver measurable impact, ranging from predictive models and enterprise automations to retrievalaugmented assistants and largescale generative AI solutions.

Innovation, iteration, and continuous improvement are core to how we work. We build, test, refine, and deploy AI capabilities that push boundaries and elevate FIG's intelligence ecosystem. As we scale the use of AI across the business, we also uphold strong governance, responsibleuse standards, and transparency to ensure our systems remain safe, ethical, and hightrust.

YOUR ROLE:

As a Senior Machine Learning/AI Engineer, you play a critical role in architecting, building, and operationalizing FIG's next generation of intelligent systems. You will develop productiongrade machine learning models, generative AI capabilities, and automated workflows that support advisors, enhance internal operations, and drive organizational efficiency.

You will:

  • Design, build, and deploy machine learning models and AI systems at scale.
  • Develop LLMpowered applications, including RAG pipelines, agent workflows, and automated decisionsupport tools.
  • Collaborate with crossfunctional partners to translate business needs into technical AI solutions.
  • Work closely with data engineering to ensure strong data availability, quality, and ML readiness.
  • Mentor engineers and analysts, guiding best practices in MLOps, model development, and responsible AI.
  • Implement monitoring, observability, and model governance frameworks.
  • Maintain high standards for security, safety, and compliance aligned with FIG's AI governance.
  • Evaluate new models, tools, and frameworks to continuously expand FIG's AI capabilities.
  • Present recommendations, insights, and solution designs to technical and nontechnical stakeholders.

WHY YOU ARE THE RIGHT PERSON:

  • You thrive in a fastpaced, highly collaborative environment.
  • You are a builder at heart-creative, curious, and excited by solving complex technical problems.
  • You blend strong engineering fundamentals with practical ML/AI expertise.
  • You understand how to design models that solve real business problems and scale effectively.
  • You are passionate about mentorship and leveling up the technical skillsets around you.
  • You communicate clearly and can explain complex concepts to nontechnical audiences.
  • You bring a forwardthinking mindset, constantly seeking opportunities to innovate and automate.
  • You embrace iteration and continuous improvement in everything you build.
  • You believe in responsible AI and understand the importance of governance, safety, and human oversight.

WHAT YOU BRING:

ย Technical Skills

  • Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikitlearn).
  • Experience building and deploying machine learning models into production environments.
  • Handson experience working with large language models (LLMs), transformers, vector databases, embeddings, and retrievalaugmented generation (RAG).
  • Ability to design endtoend AI pipelines from data ingestion and feature engineering to training, evaluation, deployment, and monitoring.
  • Familiarity with prompt engineering, finetuning, and model optimization techniques.
  • Experience implementing MLOps workflows and tools (MLflow, Databricks, Weights & Biases, SageMaker, AgentCore or similar).
  • Knowledge of agent frameworks (Strands, LangChain, Semantic Kernel, CrewAI, AutoGen).
  • Knowledge of cloud technologies (AWS preferred), containerization and orchestration.
  • Strong SQL skills and comfort working with modern data platforms (e.g., Snowflake, Redshift, BigQuery, Synapse).
  • Experience deploying APIs, microservices, and distributed systems.

ย Analytical Skills

  • Ability to evaluate model performance, identify failure modes, and optimize for accuracy, fairness, and reliability.
  • Strong criticalthinking skills paired with creativity in designing AIdriven solutions.
  • Experience conducting exploratory analysis, model experimentation, and error analysis.
  • Ability to balance technical excellence with practical business impact.

ย Business & Communication Skills

  • Ability to translate business needs into scalable AI solutions.
  • Experience partnering with crossfunctional teams across engineering, data, operations, and leadership.
  • Strong communication skills with the ability to present complex concepts clearly.
  • Ability to mentor, guide, and influence teammates and stakeholders.

Bonus Experience (Nice to Have)

  • Experience in financial services, insurance, wealth management, or other regulated industries.
  • Prior involvement in AI governance, responsible AI frameworks, or risk assessments.
  • Experience contributing to data governance, metadata management, or model lineage documentation.
  • Familiarity with experimentation frameworks, A/B testing, or statistical modeling.
  • Working knowledge of reinforcement learning, recommendation systems, or advanced NLP techniques.