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Machine Learning Teaching Assistant Jobs in California

PayJoy

Machine Learning Director

San Francisco, CA · On-site

Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Help integrate tools such as LlamaIndex and LlamaParse into existing workflows * Assist in building ...

New

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$250K - $385K/yr

... As a Machine Learning Engineer on this team, you will be at the heart of our company ... Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable ...

Conduit

Machine Learning Engineer

San Francisco, CA · On-site

... operator-assist. * Spec and order the hardware to run it. GPUs, edge boxes, cameras, lenses ... Experience with industrial machine vision (Cognex, Keyence, Zebra / Adaptive Vision, MVTec Halcon)

New

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Help integrate tools such as LlamaIndex and LlamaParse into existing workflows * Assist in building ...

New

PayJoy

Machine Learning Director

San Francisco, CA · On-site

$300K - $321K/yr

Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

PayJoy

Machine Learning Director

San Francisco, CA · On-site

$300K - $321K/yr

Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Help integrate tools such as LlamaIndex and LlamaParse into existing workflows * Assist in building ...

New

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Help integrate tools such as LlamaIndex and LlamaParse into existing workflows * Assist in building ...

New

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All JobsMachine Learning Teaching JobsMachine Learning Teaching Assistant JobsMachine Learning Teaching Assistant Jobs in California

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 California?

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

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

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

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

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

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

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

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

Machine Learning Director

PayJoy

San Francisco, CA • On-site

Full-time

Posted 11 days ago

Job description

About PayJoy
 
PayJoy, a Public Benefit Corporation, is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success.  Our patented technology for secured credit provides an on-ramp for new customers to enter the credit system.  Through PayJoy’s point-of-sale financing and card offerings, customers gain access to a modern quality of life.  PayJoy’s credit also allows our customers to seize opportunities as micro-entrepreneurs, and acts as insurance for tough times. Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 million customers as of 2025 while achieving solid profitability for sustainable growth.
 
This role

As PayJoy’s ML Platform Director, you will lead a team of very talented Machine Learning Engineers and Software Engineers that are responsible for the end-to-end ML ecosystem at PayJoy. This includes ML infrastructure: feature stores (online and offline), model serving, ETL/feature architecture and the infrastructure that helps us serve our customers like our internal offers API.


You will bridge the gap between business strategy (Risk, Fraud, Product) and technical execution, ensuring that our ML infrastructure is scalable, secure and world-class. You are a leader who enables senior-level engineers to solve the company’s most complex problems, fostering an environment where innovation meets production-grade reliability.


You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.


Key Responsibilities

  • Define the technical roadmap for our ML platform, modeling and internal APIs infrastructure, moving beyond individual projects to oversee the long-term sustainability of our "assembly line" approach to data products and ML model + offers serving.

  • Mentor and manage a team of Staff and Senior-level ML Engineers. Foster a culture of technical excellence, focusing on system design, scalability and code quality.

  • Act as the primary liaison between Data Science/ML Engineering and business stakeholders like Risk, Fraud, Engineering and Product. Translate complex business goals into actionable technical requirements that the team can execute at scale.

  • Own the long-term vision for our ML infrastructure, including deployment, monitoring and MLOps practices. Ensure that all data products are not only performant but also maintainable and compliant with global safety standards.

  • Guide the professional growth of your direct reports, ensuring they are challenged by the right problems and supported by clear career trajectories.

  • Champion the adoption of new technologies (e.g., LLMs, graph databases) and best practices that keep PayJoy at the forefront of financial ML without sacrificing stability.


Requirements

  • PhD or master’s in Computer Science, Statistics, Engineering or a related field

  • 8+ years of hands-on experience in Data Science or ML Engineering, with at least 4+ years in a leadership role managing senior-level or staff-level engineers.

  • A proven track record of designing and delivering large-scale ML systems. You must have a deep understanding of the full ML lifecycle (from feature extraction to production monitoring) and the ability to review system designs and architecture at a high level.

  • Ability to identify bottlenecks in global ML operations and design systematic solutions. You think in terms of platforms, not just individual models.

  • Exceptional ability to communicate complex technical concepts to non-technical stakeholders. You can defend technical decisions to executive leadership and advocate for the "engineering mindset."

PayJoy is proud to be an Equal Employment Opportunity employer and we welcome and encourage people of all backgrounds. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
 
PayJoy Principles
 
Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening

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.