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Live In Ai Validation Jobs in Boston, MA (NOW HIRING)

Deloitte

Model Validation Consultant

Boston, MA · On-site

Regulatory & Financial Risk - Consultant - Model Validation Our Deloitte Regulatory, Risk ... Experience supporting GenAI or Agentic AI solutions in production * Understanding of AI, GenAI, and ...

Deloitte

Model Validation Consultant

Boston, MA · On-site

Regulatory & Financial Risk - Consultant - Model Validation Our Deloitte Regulatory, Risk ... Experience supporting GenAI or Agentic AI solutions in production * Understanding of AI, GenAI, and ...

C10 Labs

Founder in Residence

Cambridge, MA · On-site +1

Identify and validate high-impact problems in healthcare, biology, and scientific systems * Develop and test new venture concepts leveraging AI, data, and emerging technologies * Rapidly prototype ...

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All JobsLive In Ai Validation JobsLive In Ai Validation Jobs in Boston, MA

Live In Ai Validation information

See Boston, MA salary details

$24

$56

$84

How much do live in ai validation jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for live in ai validation in Boston, MA is $56.49, according to ZipRecruiter salary data. Most workers in this role earn between $42.84 and $68.70 per hour, depending on experience, location, and employer.

What is a live in AI validation job?

Live In AI Validation jobs involve working closely with artificial intelligence systems to test, review, and improve their performance in real-world settings. Professionals in this role typically monitor the outputs of AI algorithms, validate data quality, and provide feedback to ensure the AI operates accurately and ethically. These jobs may require living on-site or being embedded in environments where the AI is deployed, such as smart homes, research labs, or automated facilities. The goal is to bridge the gap between AI development and real-world application, ensuring the technology is reliable and effective.

What are the key skills and qualifications needed to thrive as a live in AI validation specialist?

To thrive as a Live In AI Validation Specialist, you need a solid background in computer science, data analysis, and machine learning concepts, often supported by a relevant degree or equivalent experience. Familiarity with tools such as Python, TensorFlow, and data annotation platforms, as well as an understanding of AI validation protocols, is typically required. Attention to detail, critical thinking, and strong communication skills are essential soft skills for ensuring accurate validation and effective collaboration with development teams. These competencies are crucial for maintaining AI system quality, reliability, and alignment with real-world requirements.

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

Professionals in Live-In AI Validation often encounter challenges such as managing large-scale data collection in real-time environments and ensuring the accuracy of AI outputs in dynamic, real-world settings. Collaboration with data scientists, engineers, and end users is key to troubleshooting unexpected behaviors and improving system reliability. Strong communication and adaptability help team members quickly respond to new scenarios or hardware changes during validation. Staying up-to-date with the latest AI validation tools and continuous feedback loops can also significantly enhance the effectiveness of the validation process.

What is the difference between Live In Ai Validation vs Live In Data Entry?

AspectLive In Ai ValidationLive In Data Entry
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, client-facing, flexible hoursRemote, client-facing, flexible hours
Industry UsageAI, tech, data servicesVarious industries, administrative tasks
Common Search IntentAI validation, data verification jobsData entry, administrative jobs

Live In Ai Validation involves verifying and validating AI-generated data to ensure accuracy, often requiring critical thinking and familiarity with AI tools. In contrast, Live In Data Entry focuses on inputting data into systems, emphasizing speed and accuracy. Both roles are remote and require similar skills but serve different functions within the data management industry.

What are popular job titles related to Live In Ai Validation jobs in Boston, MA?

For Live In Ai Validation jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Live In Ai Validation jobs in Boston, MA look for?

The top searched job categories for Live In Ai Validation jobs in Boston, MA are:

What cities near Boston, MA are hiring for Live In Ai Validation jobs?

Cities near Boston, MA with the most Live In Ai Validation job openings:

Live In Ai Validation jobs near you
Infographic showing various Live In Ai Validation job openings in Boston, MA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $117,497 per year, or $56.5 per hour.

Adjunct Instructor in AI and Automation in Talent Strategy

Brandeis University

Waltham, MA • On-site

$6.5K/mo

Part-time

Re-posted 17 days ago

Job description

Brandeis University's Online Industrial Organizational Psychology Program is seeking an Adjunct Faculty member for RIOP 150 AI and Automation in Talent Strategy for the Fall 2 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Industrial Organizational Psychology.
This course will explore evidence-based approaches to diagnosing systemic barriers, designing Workplace Inclusion and Diversity interventions, measuring inclusion and belonging, and establishing accountability systems for organizational change.
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 (Master's, Ph.D. or PsyD) in Industrial-Organizational Psychology, Psychometrics, Statistics, Applied Psychology, Human Resource Management (with a quantitative focus), Behavioral Science, Data Science, User Experience, UX/UI Design, Organizational Leadership, Business Administration, , or a related field.
    • Minimum 2 years professional experience within diverse industries or sectors, with a focus on HR/people/workforce analytics, HR business partnering or strategy development (with quantitative focus), talent management (with quantitative focus), organizational development/effectiveness, personnel or workplace research, applied data science or related roles.
    • Strong knowledge of methods used to build and evaluate listening system architecture including surveys, interviews and focus groups, incorporating ethics, privacy, and legal considerations, utilizing qualitative and quantitative EX research practices including EX journey mapping, storytelling with data, human-centered design frameworks, and rapid prototyping skills, creating EX personas, diagnosing friction points, and leading equitable EX redesigns supported by data.
    • 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
    • Familiarity with online education platforms and course development tools.

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 June 1, 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 positon 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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