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Temporary Ai Data Annotation Jobs in Colorado (NOW HIRING)

Principal AI/ML Engineer

Englewood, CO · On-site

$75 - $80.15/hr

Englewood, CO Duration: 6 Months Temp to Hire Pay: $80.15/hr. on W2 Job Summary We are seeking a ... Data management and governance * Model development and versioning * CI/CD for machine learning

Lead the evaluation of alternative and temporary power solutions, such as distributed generation or ... Demonstrate willingness and capability toleverageemerging technology, automation, and AI tools to ...

Lead the evaluation of alternative and temporary power solutions, such as distributed generation or ... Demonstrate willingness and capability toleverageemerging technology, automation, and AI tools to ...

We equip agencies, MGAs, and carriers with the core digital systems, specialized AI, and data ... Additional Requirements and Details: · This is a temporary role expected to be needed through the ...

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Temporary Ai Data Annotation information

What are Temporary AI Data Annotation jobs?

Temporary AI Data Annotation jobs involve labeling, categorizing, or tagging data such as images, text, audio, or video for the purpose of training artificial intelligence (AI) and machine learning models. These roles are often short-term or contract positions, as they are needed for specific projects or during certain stages of data processing. Annotators play a critical role in ensuring the quality and accuracy of datasets, which directly impacts the performance of AI systems. No advanced technical skills are usually required, but attention to detail and consistency are important. These jobs may be offered remotely or on-site, depending on the employer.

What is the difference between Temporary Ai Data Annotation vs Data Labeler?

AspectTemporary Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic skills, sometimes specific software knowledge
Work EnvironmentRemote or on-site, project-basedRemote or on-site, often similar settings
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, tech sectors
Job FocusAnnotating data for AI trainingLabeling data for machine learning models

Temporary Ai Data Annotation involves short-term projects focused on preparing data for AI systems, while Data Labeler is a broader role that includes labeling various data types for machine learning. Both roles require similar skills and are used in tech industries, but Temporary Ai Data Annotation emphasizes project-based work specifically for AI training datasets.

What are the key skills and qualifications needed to thrive as a Temporary AI Data Annotation Specialist, and why are they important?

To thrive as a Temporary AI Data Annotation Specialist, you need keen attention to detail, strong analytical skills, and the ability to follow complex guidelines, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools like Labelbox or Prodigy, and basic computer literacy are typically required. Reliability, consistency, and the ability to work independently stand out as valuable soft skills in this role. These competencies are essential for producing high-quality, accurate data that directly impacts the effectiveness of machine learning models.

What are some common challenges faced in a Temporary AI Data Annotation role, and how can they be managed?

One of the main challenges in a Temporary AI Data Annotation position is maintaining consistent accuracy and attention to detail, especially when working with large volumes of data. Annotation guidelines can be complex and may change depending on project requirements, so adaptability and clear communication with the team are key. Managing repetitive tasks while ensuring high-quality work can be demanding, but using productivity tools and taking regular breaks can help maintain focus. Collaborating with quality assurance leads and participating in feedback sessions are also important for continuous improvement.
What are the most commonly searched types of Ai Data Annotation jobs in Colorado? The most popular types of Ai Data Annotation jobs in Colorado are:
What are popular job titles related to Temporary Ai Data Annotation jobs in Colorado? For Temporary Ai Data Annotation jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Temporary Ai Data Annotation jobs in Colorado look for? The top searched job categories for Temporary Ai Data Annotation jobs in Colorado are:
What cities in Colorado are hiring for Temporary Ai Data Annotation jobs? Cities in Colorado with the most Temporary Ai Data Annotation job openings:
AI Experience Researcher, Product Evaluation, Vision Products Group

AI Experience Researcher, Product Evaluation, Vision Products Group

Apple

Boulder, CO

$137K - $250K/yr

Full-time

Medical, Dental, Retirement

Re-posted 20 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

We are seeking a highly motivated and analytical AI Experience Researcher to join our team. This role blends cognitive and human sciences, data sciences, systems design, and product evaluation to ensure AI-powered products deliver exceptional and intuitive customer experiences.
You will work alongside a small but impactful team, collaborating with ML and data scientists, software engineers, designers, project managers, and other cross-functional teams at Apple to define success criteria for AI experiences, and create rigorous evaluations that measure these criteria in iterative product development cycles. If you're passionate about applying scientific rigor to real-world problems, thrive on innovation, and want your work to impact hundreds of millions of users, this role offers an exceptional opportunity to make a lasting contribution to products people use every day.
Description
The central challenge of this role is figuring out what "good" means for an AI experience, and then designing rigorous evaluations that measure those qualities reliably and at scale. This requires both deep theoretical grounding in human experience and a solid analytical mindset to operationalize that understanding into scalable evaluation frameworks.
Leaning on research in human sciences, you will decompose complex AI interactions into their constituent parts, reason about how those parts interact, and build evaluation frameworks that hold up under the scrutiny of non-deterministic nature of AI experiences and the pressures of iterative product development. You will derive experimental designs, create golden data sets, write tests, and turn them into prompts for LLM judges or instructions for human raters. You will run automated evaluations, analyze results, and present findings to diverse stakeholders.
Candidates who bring both quantitative rigor and a qualitative sensibility - to recognize patterns in model behaviors and outputs, and to develop an interpretive understanding of what the data is and isn't capturing from a human perspective - will thrive in this role.What matters most is the ability to hold both orientations at once - to think carefully about what makes an experience work, and to measure complex human dimensions with precision. We are also looking for someone who is excited to co-create what this discipline looks like going forward - bringing intellectual curiosity and a point of view about where human-centered AI evaluation should be headed.","responsibilities":"Develop scalable automated evaluation methodologies by operationalizing complex multi-modal multi-turn AI experiences into observable and measurable metrics that work across diverse use cases, features, or product area
Produce comprehensive evaluation plans detailing evaluation scope, validation and data strategy, tooling requirements, resource allocation, and timelines
Derive experimental designs and write test instructions for LLM judges or for human raters
Define requirements for, or curate datasets that represent realistic usage; support data generation and annotation workflows to ensure coverage, quality, and alignment with product goals
Implement and analyze automated evaluations, maintaining rigor around reproducibility, identifying key insights, and areas for improvement across both qualitative and quantitative patterns
Prepare and present clear, concise, and impactful evaluation findings to diverse stakeholders, translating results into actionable recommendations for model training, ranking, and product decisions
Partner with engineers, QA, data scientists, designers, and product managers throughout the product development lifecycle to integrate evaluation insights and drive continuous improvement
Contribute to evolving human-centered AI evaluation methodologies and help to define best practices for AI experience evaluation as the field matures
Preferred Qualifications
Familiarity with methods for capturing experiential quality beyond task success - such as cognitive interviews, think-aloud protocols, interaction analysis, or discourse and conversation analysis
Experience designing and implementing automated evaluation pipelines, including writing prompts for LLM judges and constructing human-in-the-loop or multi-turn evaluation setups
Experience working with multimodal or agentic systems, AI/ML models, preferably Large Language Models
Familiarity with automated testing frameworks and tooling
Experience with data generation and annotation workflows, including curating datasets, scenarios, and tasks that represent realistic usage
Portfolio demonstrating previous evaluation frameworks, research findings, or measurable contributions to product improvement
Background in learning sciences or instructional design, with experience reasoning about what makes a complex human experience effective is a plus
Minimum Qualifications
Advanced degree in Cognitive Psychology, Human-Computer Interaction (HCI), User Experience (UX) Research, Learning Sciences, Learning Analytics, Psychometrics, Applied Behavioral Science, or a related field with a focus on human cognition, behavior, and empirical evaluation
A strong data-driven mindset with experience designing and conducting rigorous empirical research or evaluation - including experimental design, data analysis, and interpretation of various qualitative and quantitative data - particularly in the context of complex human-system interactions
Ability to reason from theoretical grounding about what makes an experience good in a given context, and to translate that reasoning into evaluation frameworks and measurement designs
Demonstrated ability to operationalize research literature, qualitative user feedback, and quantitative behavioral data into actionable evaluation criteria, observable metrics, and product insights
Proficiency in data analysis and interpretation, with a strong understanding of statistical validity in evaluation contexts
Exceptional collaboration skills with a track record of working effectively in cross-functional teams that include engineering, ML, design, QA, leadership, and subject matter experts of diverse domains
Strong communication skills, with the ability to translate complex research findings and evaluation results into clear, actionable recommendations for both technical and non-technical audiences
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $137,500 and $250,700, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976