Interested in this AI/ML Engineer role at California Institute of Applied Technology?
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About This Role
At the heart of our work is a simple belief: We are passionate about education and student success. We're hiring to help bring that belief to life through thoughtful execution, partnership, and a strong commitment to the people we serve.
Schedule \-Class schedule works well even if you already have a daytime job.
Work from Home (WFH) \- *Remote work must be performed while residing in California, New Mexico, Florida or Massachusetts*
CIAT Campus Locations: San Diego, CA and Albuquerque, NM
Reports to: Associate Dean \- Cloud Administration Program
Status: Non\-Exempt
Employment Type: Variable\-Hour (Part\-Time)
Are you passionate about positively changing the lives of others? California Institute of Applied Technology (CIAT) is growing and seeking educators and professionals with a passion for mentoring others. If this is you, please contact us! CIAT prepares students for professional success by offering practical training in today's most competitive technology fields to make sure students are job ready. With a large selection of courses, flexible schedules, and an online campus, we aim to empower the working student. We are laser\-focused on student success, whether just starting out, making a career change, or transitioning into civilian life, CIAT prepares students for success!
Essential Duties and Responsibilities:
Teaching:
- Available to teach synchronous online courses via Microsoft Teams
- Plan and organize instruction in ways that maximize student learning and engagement
- Modify, where appropriate, instructional methods and strategies to meet diverse student's needs
- Employ appropriate teaching and learning strategies to communicate subject matter to students via a synchronous online format (Microsoft Teams)
- Current certifications in subjects taught
Mastery of Subject Matter:
- Demonstrate a thorough and accurate knowledge of their field or discipline
- Connect their subject matter with related fields
- Stay current in their subject matter through professional development, through involvement in professional organizations, and attending professional meetings, conferences, or workshops
Adhering to College Policies and Procedures:
- Ensure Student Database is fully updated and accurate at all times regarding student grade record information
- Maintain compliance with accreditation related to instructional and the quality of education, scheduled class hours requirements and CIAT policies and procedures
- Promote collaboration with other staff members and participate in the implementation of new projects, ideas, etc.
- Adhere to the CIAT business casual attire. Please refer to the CIAT Employee Handbook for the complete policy. Clothing should be neat, clean, and without rips and holes. We can accommodate polo shirts
### Requirements
- Information Technology Instructors must provide official transcripts of bachelor's (or higher) degree and active/current certification on the subject being taught
- General Education Instructors must provide official transcripts of bachelor's and master's (or higher) degrees that include at least 18 units on the subject being taught
- At least three years' experience in the respective field OR two years of teaching experience
- Advanced subject matter expertise preferred in the following areas: Python programming and data science libraries (NumPy, Pandas, Matplotlib, Scikit\-learn), AI/ML fundamentals (supervised/unsupervised learning, NLP, and gen AI concepts), and familiar with Azure AI services and/or other cloud\-based AI platforms (e.g. AWS, Google Cloud)
- Synchronous online teaching experiece preferred
- Effective presentation skills
- High level of flexibility, creativity, and dependability
- Good working knowledge of MS Office applications including Microsoft Teams Word, Excel, and PowerPoint as well as learning technologies such as Canvas
- Work independently with minimal supervision
- Ability to multitask
- Problem solves rapidly and effectively, in a timely manner
- Works with a sense of urgency, while engaging and listening to coworkers from other departments
- Ability to work collaboratively with colleagues, academic departments, and administration to support student success, achieve institutional goals and contribute to a positive and inclusive culture
- Commitment to fostering an inclusive and supportive learning environment that respects the diversity of students' backgrounds, experiences, and perspectives
- Knowledge of current trends, best practices, and didactic approaches in higher education
- Demonstrated ability to deliver engaging and effective lesson plans that meet the diverse needs of students
- Strong communication skills, both verbal and written, with the ability to effectively convey information and interact with students, colleagues, and others
- Compliance with all college policies, procedures, and regulations, including those related to academic integrity, student conduct, and instructional delivery
- Adhere to CIAT's compliance requirements to ensure all Federal, State, accreditation, and institutional policies and procedures are being met
- Follow communication guidelines to ensure high levels of customer satisfaction and professionalism
- Must be able to embody CIAT's mission, vision, purpose and values
Position Type and Expected Hours of Work
This is a variable hour position. Days and hours of work are usually Monday through Friday, but weekend and evening hours are required. Live classes are scheduled twice a week (Monday and Tuesday) from 6:00pm\-9:30pm (Pacific Time).
Supervisory Responsibility
This position has no supervisory responsibilities.
Values
Values such as integrity, excellence, customer service, teamwork and mutual respect are some of those that remain constant, regardless of changes in our company. When identifying company values, it is important that those values are being demonstrated in the course of business each day. Our values set expectations for how employees and managers interact with every person while representing the company.
- We are passionate about education and student success
- We value integrity and excellence in our employees and students
- We treat ourselves and our students with dignity and respect
- We believe in and encourage innovation at our school to better help our students succeed
- We have a customer centric focus and we want people highly committed to achieving goals, where our success equals student's success
- We are accountable for our actions and focus on improvements moving forward
- We have a growth mindset with a sincere belief that every student can do better and achieve their goals
- We expect every employee to be an example of conduct and professionalism, being a role model to students and colleagues
- We commit to an inclusive and supportive learning environment that respects the diversity of students' backgrounds, experiences, and perspectives
- We foster lifelong learning and professional development
Physical Demands
These physical demands are representative of the physical requirements necessary for an employee to successfully perform the essential functions of the job. Reasonable accommodation can be made to enable people with disabilities to perform the described essential functions:
- Essential functions of this role require sitting for extended periods of time
- Ability to type, use a computer to search for information and input information while speaking on the phone is required
- The employee will frequently be required to use the computer, mouse and telephone to conduct the regular tasks of this role
- The employee will be required to compute simple to simple mathematical calculations as a normal part of this role
Work Environment
While performing the responsibilities of this remote position, the job holder will work in a home office environment. Reasonable accommodation may be made to enable people with disabilities to perform the essential functions of the job. This role routinely involves using standard office equipment such as computers, phones, and virtual communication tools. Employees are expected to ensure that their home office is a safe and ergonomic working environment.
Employees must maintain data security and confidentiality in accordance with company policies and use secure connections for all work\-related activities. Expectations regarding work hours, availability, and time tracking will be clearly communicated and must be adhered to.
The company is not responsible for maintaining home office environments beyond the provision of reasonable accommodation and necessary work\-related equipment. Workers' compensation and liability for injuries that occur in the home office will be covered as per company policy and applicable laws.
This remote work policy is designed to comply with all relevant local, state, and federal laws.
AAP/EEO Statement
California Institute of Applied Technology provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, California Institute of Applied Technology complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
California Institute of Applied Technology expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of California Institute of Applied Technology's employees to perform their job duties may result in discipline up to and including discharge.
California Institute of Applied Technology California Institute of Applied Technology California Institute of Applied Technology.
Other Duties
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time, with or without notice.
We know great candidates may not meet every single qualification listed. If this role speaks to you and you believe you could thrive here, we welcome your application.
Salary Context
This $79K-$89K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At California Institute of Applied Technology, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($84K) sits 61% below the category median. Disclosed range: $79K to $89K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
California Institute of Applied Technology AI Hiring
California Institute of Applied Technology has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $89K - $89K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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