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$22.7K

$52.8K

$98.2K

How much do machine learning teaching jobs pay per year?

As of Jul 10, 2026, the average yearly pay for machine learning teaching in California is $52,775.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,400.00 and $59,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Teaching position, and why are they important?

To thrive in a Machine Learning Teaching role, you need in-depth knowledge of machine learning concepts, proficiency with programming languages like Python or R, and an advanced degree in computer science or a related field. Experience with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and familiarity with curriculum development and teaching technologies are typically required. Strong communication, patience, and the ability to clearly explain complex topics make educators especially effective. These skills ensure students gain practical expertise and solid theoretical foundations, preparing them for real-world machine learning careers.

What are the typical responsibilities of a Machine Learning Teaching professional?

Machine Learning Teaching professionals are responsible for designing and delivering lessons on core machine learning principles, guiding students through practical projects, and assessing their progress. They may create course materials, conduct lectures and labs, and offer mentorship to students on capstone or research projects. Collaboration with other faculty or industry experts is common for curriculum updates and staying current with advancements in the field. Additionally, they often provide feedback, support diverse learners, and help students connect theory with real-world applications, ensuring a comprehensive educational experience.

What is a Machine Learning Teaching job?

A Machine Learning Teaching job involves educating students or professionals about machine learning concepts, algorithms, and applications. Responsibilities may include designing curricula, delivering lectures, conducting hands-on coding sessions, and mentoring learners. These roles exist in universities, online education platforms, and corporate training programs. Strong knowledge of machine learning frameworks, programming (e.g., Python, TensorFlow, PyTorch), and effective teaching skills are essential for success.

What is the salary of machine learning trainer?

The salary of a machine learning trainer varies based on experience, location, and employer, but typically ranges from $60,000 to $120,000 annually. Professionals with advanced skills in programming, data analysis, and deep learning tools like Python, TensorFlow, or PyTorch tend to earn higher salaries.

Which 3 jobs will survive AI?

Machine Learning Teaching roles are likely to persist as they involve explaining complex concepts, mentoring, and adapting to new AI tools. Jobs requiring emotional intelligence, creativity, and critical thinking—such as healthcare professionals, educators, and skilled tradespeople—are also expected to remain in demand despite AI advancements.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills, extensive experience, and sometimes leadership responsibilities. These roles usually involve developing innovative AI solutions, managing teams, and working with cutting-edge tools and frameworks, with compensation reflecting the expertise and impact expected.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation can handle certain tasks, MLEs are essential for creating, optimizing, and troubleshooting complex models. AI tools may augment their work, but the role requires expertise in data science, programming, and domain knowledge that cannot be fully replaced by AI itself.
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:
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What cities in California are hiring for Machine Learning Teaching jobs? Cities in California with the most Machine Learning Teaching job openings:
Machine Learning Teaching jobs near you
Adjunct Instructor in Machine Learning Engineering and MLOps

Adjunct Instructor in Machine Learning Engineering and MLOps

Brandeis University

Brandeis, CA • On-site

$6.5K/mo

Part-time

Re-posted yesterday

Job description

Brandeis University's Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 110 Machine Learning Engineering and MLOps for the Fall 1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics.

Course Description This course focuses on the end-to-end ML lifecycle-feature stores, CI/CD pipelines, containerization, and model monitoring emphasizing responsible, scalable deployment.

Core Course Responsibilities Summary

  • Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.

  • Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.

  • Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.

  • Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:

  • Required:

    • Advanced degree (Masters or Ph.D) in Computer Science, Data Science, or Software Engineering)

    • Industry experience in MLOPS, ML Platform development, production of ML systems or related fields.

    • Experience in end-to-end machine learning engineering, including feature engineering model training, containerization, model monitoring, and responsible deployment practices.

    • At least 1 year of teaching or training experience (preferably online/asynchronous)

    • Experience with online instruction

    • Excellent communication and teaching skills in an online learning environment.

  • Preferred:

    • Prior online teaching experience at the graduate level

    • Knowledge of global learner personas and culturally responsive pedagogy

    • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Interested candidates should submit:

A cover letter highlighting relevant qualifications and teaching experience.

A current CV or resume.

Contact information for three professional references.

Application review begins 5/27/2026 though we will continue to accept submissions on an ongoing basis.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.

Compensation for this position is $6573.15

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

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