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Overnight Artificial Intelligence Testing Jobs in Springfield, VA

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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 are the typical challenges faced in overnight artificial intelligence testing, 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 are the key skills and qualifications needed to thrive in overnight artificial intelligence testing, 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 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.

How do I become an overnight artificial intelligence testing?

To become an overnight artificial intelligence tester, you should have strong programming skills, experience with AI and machine learning models, and familiarity with testing tools and environments. Typically, this role involves working in shifts to monitor, evaluate, and troubleshoot AI systems during off-hours, requiring attention to detail and problem-solving abilities.

What cities near Springfield, VA are hiring for Overnight Artificial Intelligence Testing jobs?

Cities near Springfield, VA with the most Overnight Artificial Intelligence Testing job openings:

Artificial Intelligence Engineer

Triumph Enterprises, Inc

Washington, DC โ€ข On-site

$150 - $200/hr

Other

Posted 2 days ago

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Job description

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Triumph Enterprises is building the team for a Department of Veterans Affairs Office of Information and Technology / Office of Information Security (OIT/OIS) program covering enterprise cybersecurity architecture and engineering. We are seeking an Artificial Intelligence Engineer to apply machine learning and large language models to cybersecurity operations and to own the evaluation methodology that determines whether an AI capability is fit to deploy.

Program: VA Cybersecurity Architecture and Engineering Services (COSE)
Location: Washington, DC (Remote) | Full-Time, Exempt | Contingent upon contract award

This is a build-and-prove role in equal measure. Our technical approach commits to a six-pillar validation framework applied before any AI capability is deployed, with testing mapped to each pillar. The engineer in this seat is accountable both for the automation that gets built and for the defensible evidence that it should be trusted in a Federal security environment.

RESPONSIBILITIES
  • - Design, build, and operate AI and machine learning capabilities supporting cyber tool integration and security operations automation.
  • - Own the six-pillar AI validation framework: categorize, test, and validate AI technologies before deployment, with testing traceable to each pillar.
  • - Deliver the Autonomous Workflow Library, jointly with the DevSecOps Engineer.
  • - Produce the quarterly Security Control Effectiveness Report.
  • - Maintain the AI System / LLM Development and Operation Documentation Package.
  • - Issue AI Model / LLM Change Disclosures no later than 30 days prior to any model change.
  • - Meet the AI attestation and disclosure obligations the program carries, and document model behavior and changes for a Government audience.
  • - Partner with the Cloud Security Architect and DevSecOps Engineer to integrate AI capability into the enterprise security toolset without expanding the attack surface.
REQUIRED QUALIFICATIONS
  • - Minimum 10 years of information technology experience, with demonstrated applied machine learning or LLM engineering in a security or operations context.
  • - Master's degree in Cybersecurity, Computer Science, Information Systems, Information Assurance, Information Security, Data Science, or a related field.
  • - A defensible, documented methodology for categorizing, testing, and validating AI technologies prior to deployment.
  • - Working knowledge of Federal AI governance obligations, including attestation and disclosure requirements.
  • - Ability to write model behavior and change documentation that will stand up to Government review.
  • - Proficiency in Python and modern ML/LLM tooling, and the engineering discipline to move a model from prototype to a supportable production capability.
CERTIFICATION (REQUIRED)

One or more of the following: Information Assurance Technician (IAT) III, Information Assurance Management (IAM) III, or Information Assurance System Architect and Engineer (IASAE) III. Commonly satisfied by CISSP, CISSP-ISSEP, CISM, or CASP+. Certification is verified against the current DoD 8140 qualification matrix before an offer is extended. The credentials named above are those most commonly held; any other credential on the current matrix at the required level also qualifies.

Note to applicants: this combination -- senior AI/ML engineering plus a DoD 8570 Level III certification -- is uncommon. If you hold the technical depth and are actively pursuing the certification, we want to talk to you.

This position requires a Tier 4 / High Risk Public Trust background investigation. A Tier 4 investigation is adjudicated for suitability and fitness and is not a security clearance. Candidates must be U.S. citizens and able to obtain and maintain the investigation, VA systems access, and PIV credentialing. No work may begin until an interim determination is received.

PREFERRED
  • - NIST AI Risk Management Framework experience.
  • - Security operations automation using large language models -- triage, enrichment, detection engineering, or response orchestration.
  • - Published or otherwise demonstrable AI evaluation methodology.
  • - Experience deploying models in a FedRAMP or Federal cloud environment.
  • - Prior VA program experience, particularly within OIT or OIS.
ADDITIONAL INFORMATION

Travel is expected to be 0-10%. This position is contingent upon contract award.

Triumph Enterprises, Inc. is an SBA-certified Service-Disabled Veteran-Owned Small Business and an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by law.

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