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Overnight Artificial Intelligence Testing Jobs (NOW HIRING)

SCATR Corp.

Artificial Intelligence Engineer

Cleveland, OH · On-site

$111K - $133K/yr

We are looking to add an experienced Artificial Intelligence (AI) Engineer to our dynamic team and ... As an AI Engineer, you will be responsible for designing, implementing, testing and maintaining ...

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Overnight Artificial Intelligence Testing information

What is overnight artificial intelligence testing?

Overnight artificial intelligence testing refers to the process of running and evaluating AI models or software systems during nighttime hours, typically when regular operations are minimal. This allows for extensive automated tests, stress checks, and data processing without disrupting daytime business activities. Testers monitor results, identify errors or performance issues, and ensure the AI systems are functioning as intended before the next business day. This role often requires knowledge of both software testing practices and AI technologies.

What is the 10 20 70 rule for AI?

The 10 20 70 rule in AI refers to a guideline for training models, suggesting that 10% of data should be high-quality labeled data, 20% should be semi-labeled or annotated data, and 70% should be unlabeled data used for unsupervised learning. For AI testing roles, understanding data distribution and quality is essential to ensure accurate model evaluation and validation.

How much do AI testers get paid?

AI testers typically earn between $50,000 and $100,000 annually, depending on experience, location, and the complexity of the testing environment. Entry-level positions may start lower, while experienced testers with skills in machine learning and automation tools can earn higher salaries.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level positions in artificial intelligence, such as AI research directors, chief AI officers, or senior machine learning executives, often requiring advanced degrees, extensive experience, and expertise in AI tools and algorithms. These roles usually involve strategic decision-making, leadership, and innovation in AI development within large organizations or tech companies.

Which 3 jobs will survive AI?

In the context of overnight artificial intelligence testing, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Roles such as AI ethics specialists, creative designers, and human-centered customer service representatives are less susceptible to automation due to their reliance on human judgment and nuanced understanding. These positions often involve skills that are difficult for AI to replicate fully.

What is the difference between Overnight Artificial Intelligence Testing vs Data Scientist?

AspectOvernight Artificial Intelligence TestingData Scientist
CredentialsTypically requires knowledge of AI tools, programming, and testing protocolsRequires degrees in data science, statistics, or related fields, often with certifications
Work EnvironmentPrimarily in labs or testing facilities, often overnight shiftsOffice or remote, with data analysis and modeling tasks
Industry UsageUsed in AI development, quality assurance, and validation processesApplied in data analysis, predictive modeling, and business insights

Overnight Artificial Intelligence Testing focuses on evaluating AI systems during overnight shifts, emphasizing testing protocols and quality assurance. Data Scientists analyze data, build models, and generate insights. While both roles involve technical skills, AI Testing is more specialized in validation processes, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as an Overnight Artificial Intelligence Tester, and why are they important?

To thrive as an Overnight Artificial Intelligence Tester, you need a solid understanding of AI concepts, software testing methodologies, and familiarity with programming languages like Python, typically supported by a degree in computer science or related field. Experience with test automation tools, version control systems (like Git), and bug tracking platforms is commonly required. Strong attention to detail, problem-solving abilities, and effective written communication are crucial soft skills for identifying issues and documenting test results. These skills ensure accurate, efficient, and reliable testing of AI systems during overnight shifts, maintaining product quality and meeting development timelines.

What are the typical challenges faced in an Overnight Artificial Intelligence Testing role, and how can they be managed?

Professionals working in Overnight Artificial Intelligence Testing often encounter challenges such as maintaining high attention to detail during late hours, managing unexpected system behaviors, and coordinating with day-shift teams for seamless issue resolution. To manage these challenges, it's important to establish clear communication protocols for handoffs, utilize monitoring tools to catch anomalies early, and follow structured testing procedures. Staying organized and taking scheduled breaks can also help maintain focus and productivity during overnight shifts.
What cities are hiring for Overnight Artificial Intelligence Testing jobs? Cities with the most Overnight Artificial Intelligence Testing job openings:
What are the most commonly searched types of Artificial Intelligence Testing jobs? The most popular types of Artificial Intelligence Testing jobs are:
What states have the most Overnight Artificial Intelligence Testing jobs? States with the most job openings for Overnight Artificial Intelligence Testing jobs include:
Overnight Artificial Intelligence Testing jobs near you
Data Scientist (Artificial Intelligence/Machine Learning)

Data Scientist (Artificial Intelligence/Machine Learning)

Defense Logistics Agency

Battle Creek, MI

Full-time

Posted 5 days ago

Defense Logistics Agency rating

8.4

Company rating: 8.4 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

159th of 649 rated public administrative organizations

Job description

Telework Eligible

Yes

Major Duties

  • Serves as an Al (Artificial Intelligence) Testing and Evaluation Data Scientist providing subject matter Al expertise and execution to test and evaluate Al systems.
  • Provides professional and scientific expertise in the application of data science disciplines for complex studies in machine learning and deep learning algorithms, statistical analysis, visualizations, programing and computer science.
  • Provides expertise in evaluating and measuring data science and artificial intelligence systems in accordance with data science Lifecyle practices within DoD parameters.
  • Ensures Al systems are developed in accordance with applicable legal frameworks such as General Data Protection Regulation (GDPR) and National Institute of Standards and Technology (NIST).
  • Incorporates, Office of Management and Budget (0MB) test and evaluation requirements, DOD Al ethical principles into DLA Al test and evaluation framework to generate an RAI test strategy for modeling cases.
  • Utilizes expertise to coordinate the integration of the DLA Al testing and evaluation program during the product lifecycle from concept and design inception, as development proceeds, and integrated to ensure effective RAI implementation.

Qualification Summary

To qualify for a Data Scientist (Artificial Intelligence/Machine Learning), your resume and supporting documentation must support: A. Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position. B. Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position. To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-after­competitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes: Conducts large, agency wide, research and development reviews of metrics, measurements, and evaluation methods for emerging and existing areas of Al. Utilizes data science expertise to develop algorithms and tools to support data manipulation and processing as well as the use of data visualization techniques to articulate high risk findings. Ensures the Al systems are designed for auditability to manage Al risk assessment policies and principles which guide automated decisions supporting DLA business operations. Provides expert advice to senior leadership and Al stakeholders to adopt new or revised policy and implementation plans resulting from Al test and evaluation integration. Assesses data quality and establishes standards to validate quality criteria for data to ensure it meets the necessary requirements for Al testing and evaluation. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

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