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Temp Ai Jobs (NOW HIRING)

Exodigo

Field Operator - Temp Position

Phoenix, AZ · On-site

$33 - $35/hr

Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete ... Availability to work Monday-Friday for a temporary 3-month assignment. Requirements * Strong ...

Exodigo

Field Operator - Temp Position

Phoenix, AZ · On-site

$33 - $35/hr

Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete ... Availability to work Monday-Friday for a temporary 3-month assignment. Requirements * Strong ...

DivcoWest

AI Intern

San Francisco, CA · On-site

$20 - $30/hr

Summary The AI Intern will join the Technology team to design and implement intelligent solutions ... The position is a temporary full-time role for one (1) year. Exact schedule can be adjusted to ...

WGA Advisors, Inc.

$165 - $193/hr

Return to Careers WGA Advisors | Temporary Project-Based Engagement (Corp-to-Corp) | Remote with ... WGA's AI Workforce Solutions practice is at the forefront of helping global enterprises move from ...

New

HME

AI Program Manager, Temporary

Carlsbad, CA · On-site

$125 - $150/hr

This role will help turn AI development strategy into practical, repeatable operating practices that improve engineering speed, quality, consistency, and measurable business impact. Key ...

helsing.ai

$90 - $120/hr

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve ... Relocation support: up to €2,500 and 4 weeks temporary accommodation * Learning: €500/£450 ...

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Temp Ai information

What are temp ai jobs?

Temp AI jobs are temporary positions that involve working with artificial intelligence technologies or projects. These roles can range from data labeling and machine learning model testing to short-term AI development or support tasks. Temp AI jobs are often project-based and may be found in industries such as technology, healthcare, finance, and more. They offer opportunities for individuals to gain experience in the rapidly evolving field of AI without committing to a permanent position.

What are some common challenges faced by professionals working in temporary AI roles, and how can they be addressed?

Professionals in temporary AI positions often face the challenge of quickly adapting to new projects and team environments due to the short-term nature of their assignments. They may need to rapidly familiarize themselves with proprietary data, tools, and workflows, as well as build relationships with team members in a limited timeframe. To address these challenges, clear communication, proactive learning, and seeking out onboarding resources are essential. Being adaptable and open to feedback can also help temporary AI professionals integrate smoothly and contribute effectively during their assignment.

What are the key skills and qualifications needed to thrive as a temporary administrative assistant, and why are they important?

To thrive as a Temporary Administrative Assistant, you need proficiency in office administration, organization, and time management, typically supported by a high school diploma or equivalent. Familiarity with office software like Microsoft Office Suite, email platforms, and sometimes scheduling or database systems is important. Strong communication, adaptability, and attention to detail help you excel in fast-changing environments and support diverse teams. These skills ensure efficient operations and seamless support, making you an asset during short-term assignments.

What is the difference between Temp Ai vs Data Analyst?

AspectTemp AiData Analyst
Required CredentialsTypically no formal degree, on-the-job trainingBachelor's degree in data science, statistics, or related field
Work EnvironmentTemporary assignments, various industriesFull-time, office or remote settings in corporate or tech sectors
Employer & Industry UsageStaffing agencies, temp agencies, project-based workCorporations, consulting firms, tech companies
Common Search & ComparisonTemp Ai vs Data Analyst

The main difference between Temp Ai and Data Analyst roles lies in their credentials and work setup. Temp Ai positions often require minimal formal education and are project-based, while Data Analysts typically hold degrees and work in permanent roles. Temp Ai offers flexibility and short-term assignments, whereas Data Analysts focus on ongoing data interpretation and reporting within organizations.

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What are the most commonly searched types of Ai jobs?

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Temp Ai jobs near you
Infographic showing various Temp Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

Instructional Staff - AI Engineer

Carnegie Mellon University

Pittsburgh, PA • On-site

Other

Posted 23 days ago

Carnegie Mellon University rating

8.8

Company rating: 8.8 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

35th of 628 rated colleges and universities

Job description

Description
Position Title: Instructional Staff - AI Engineer
Location: Heinz College, Carnegie Mellon University
Start Date: August 24, 2026 (Fall Semester)
Position Type: Part-Time, Temporary
Reports To: Faculty Supervisor(s)
Student-Facing: Yes
Position Summary
Heinz College at Carnegie Mellon University is seeking a graduate of the Master of Artificial Intelligence Systems Management (AIM) or an AI-related CMU program to assist in creating AI systems or workflows for assignments originally designed for Python developers into equivalent assignments for AI systems or LLM agent workflows. This role supports curriculum development and delivery for these courses, which include core courses in the AIM program and a related MISM course: 95-820 NL(X) and LLMs, 94-844 Generative AI Lab, 95-864 AI Model Development, and 94-879 Fundamentals of Operationalizing AI.
Key Responsibilities
Manage software, data and AI model compliance, including understanding university, local, state and federal policies to ensure course content, computing environments, computer resources, data, information and course delivery meets university, local, state and federal rules.
Establish, develop and maintain shared compute resources, such as virtual machines or local hosts, for implementing and evaluating Generative AI models.
Develop course assignments and activities to teach Generative AI model development, evaluation, operationalization, and standard industry practices for AI engineering.
Translate existing Python programming assignments into LLM Agent or 'Agentic AI' equivalents.
Collaborate with a supervising professor to align assignments with course objectives.
Maintain clear documentation of decisions and code structure.
Assist in testing and validating translated assignments for correctness and usability.
Additional Information
This is a student-facing, full-time temporary role focused on backend curriculum support.
The position is ideal for someone looking to contribute to academic development while gaining experience in educational technology and instructional design.
This is an AI-engineering focused position, supporting AI courses at Heinz College, Carnegie Mellon University. The position is ideal for someone who enjoys building systems, workflows or APIs for large language model (LLM) systems.
Qualifications
Required Qualifications
Graduate of the AIM program at Heinz College, Carnegie Mellon University.
Willingness to present or communicate with students on a regular basis.
Proficiency in Python programming language and LLM System Engineering.
Experience establishing virtual machine and compute environments (Linux, AWS, Google Cloud Platform).
Strong understanding of distributed AI system concepts and infrastructure.
Experience with designing and conducting LLM evaluations and working with LLM APIs.
Ability to work independently and communicate effectively with faculty supervisor(s).
Ability to conduct worth with integrity and ethics and work professionally with students.
Preferred Qualifications
Experience with educational content development or curriculum support.
Experience with version control systems (e.g., Git).
Experience working with containers (Docker, Podman, Apple Containers)
Attention to detail and commitment to producing high-quality instructional materials.

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