Technical Instructor (AWS Machine Learning)
Per Scholas
| Company | Per Scholas |
| Category | Data & Analytics |
| Location | United States |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 22 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
ABOUT PER SCHOLAS:
For 30 years, Per Scholas has been on a mission to drive mobility and opportunity in the ever-advancing technology landscape by unlocking the untapped potential of individuals, uplifting communities, and meeting the needs of employers through rigorous tech training. By teaming up with dynamic employer partners, ranging from Fortune 500 companies to innovative startups, we're forging inclusive tech talent pipelines, fulfilling an ever-increasing need for skilled talent. With national remote training and campuses in 20+ cities and counting, Per Scholas offers no-cost training programs in the most sought-after tech skills, spanning Cloud, Cybersecurity, Data Engineering, IT Support, Software Engineering, and more. To date, 30,000+ individuals have been trained through Per Scholas, propelling their professional trajectories into high-growth tech careers with salaries three times higher than their pre-training earnings. Learn more by visiting PerScholas.org and follow us on LinkedIn , X , Facebook , Instagram , and YouTube .
Per Scholas preferred hires reside within the following states : AZ, CA, CO, FL, GA, IL, IN, KS, MD, MA, MI, MO, NC, NJ, NY, OH, PA, TX, WA POSITION TITLE: AWS Machine Learning - Instructor
DURATION: Part-Time Contract Role
COMPENSATION: $65/hour
WHO WE’RE LOOKING FOR
Per Scholas is seeking an AWS Machine Learning instructor to become a member of our team. The ideal candidate is a detail-oriented, problem-solving individual with strong technical and instructional skills, demonstrates the ability to adapt quickly to a dynamic environment, and maintains a strong sense of accountability. To succeed in this role, candidates must be business-minded within our mission focus and excel in instructional delivery that meets clients’ and learners’ high expectations.
WHAT YOU’LL DO
Support instructor-led training that prepares students for entry-level to mid-level careers in AI and Machine Learning infrastructure on AWS. Responsibilities include daily instruction, assessment administration, attendance, one-on-one tutoring, daily evaluation and monitoring of individual student progress, addressing student violations with students in a consistent manner, and more.
Provide students with access to relevant resources for outside learning on technologies and study aids relevant to the curriculum.
Work closely with the team to identify student needs, provide the necessary support, establish individualized plans for student achievement, and participate in regular student-status meetings.
Maintain and update Salesforce and/or our LMS with student grades, certification scores, and progress notes.
Support and maintain the training curricula, syllabi, lesson plans, and other classroom materials.
WHAT YOU’LL BRING TO US
Instructional Skill Sets
1-3 years of teaching or training experience
Strong technical background; able to grasp and convey highly technical subject matter
Ability to respond clearly to live digital conversations via a digital engagement platform such as Zoom or an in-person training environment.
Strong communication skills
Required Skill Sets
ML Development & Tools : Hands-on expertise with Amazon SageMaker, AWS Bedrock, and SageMaker Studio.
Data Engineering : Proficiency in ingesting and transforming datasets using AWS Glue, S3, and SageMaker Data Wrangler.
MLOps Orchestration : Expertise building automated ML pipelines using AWS Step Functions, SageMaker Pipelines, and CI/CD workflows.
Security & Governance : Strong understanding of IAM policies, VPC security, and auditing via CloudWatch and CloudTrail.
Model Monitoring : Ability to evaluate performance and bias using SageMaker Clarify and Model Monitor.
Generative AI Integration : Ability to demonstrate the use of LLMs and Copilots for debugging code, generating notes, and automating te
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