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Overnight Artificial Intelligence Testing Jobs (NOW HIRING)

MarketOnce

Artificial Intelligence Engineer

Denver, CO · On-site

$140K - $175K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

About the Opportunity: We are seeking an experienced Artificial Intelligence Engineer who ... testing, including annotation and evaluation tooling * Collaborate with product managers to ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

  • Medical

  • Dental

  • Vision

  • PTO

We are seeking an Artificial Intelligence Engineer III to join our team Summary: This position is ... Advanced proficiency in software engineering, including Python, APIs, testing, and system design.

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

  • Medical

  • Dental

  • Vision

  • PTO

We are seeking an Artificial Intelligence Engineer III to join our team Summary: This position is ... Advanced proficiency in software engineering, including Python, APIs, testing, and system design.

Insperity

Artificial Intelligence Engineer I

Kingwood, TX · On-site

  • Medical

  • Dental

  • Vision

  • PTO

The Artificial Intelligence Engineer I focuses on building strong SQL and data management ... Follows established testing, documentation, security, and deployment practices to ensure production ...

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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 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

AVP, Artificial Intelligence

Credit One Bank

Las Vegas, NV • On-site

Other

Re-posted 21 days ago

Job description

Description
Position Summary
The Assistant Vice President of Artificial Intelligence (AVP of AI) is responsible for leading delivery and execution of AI and machine learning capabilities within a regulated banking, credit card, and financial services environment. Reporting to the VP of AI, this role acts as a hands-on technical leader and people manager for AI Engineers, ensuring AI solutions drive fraud prevention, credit risk management, customer experience personalization, and operational efficiency while meeting regulatory, privacy, and model risk requirements.
Essential Job Functions
  • Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
  • Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
  • Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
  • Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
  • Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
  • Oversee model validation, explainability, bias testing, and audit readiness.
  • Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.

Position Requirements
Core AI Concepts and Technologies Required:
  • Machine Learning & Modeling
    • Supervised, unsupervised, reinforcement learning
    • Deep learning (CNNs, RNNs, Transformers)
    • Natural Language Processing (NLP) & LLMs
    • Generative AI (diffusion models, fine-tuning, RAG)
    • AI Engineering & MLOps

  • AI Engineering & MLOps
    • Model training, deployment, monitoring, and retraining
    • Feature stores, vector databases, and model registries
    • CI/CD pipelines for ML (MLOps)
    • GPU/accelerator compute architectures

  • Cloud & Infrastructure
    • Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI
    • Kubernetes, containerization, microservices
    • Data platforms (Databricks, Snowflake, Synapse)

  • Responsible AI & Governance
    • Model explainability (SHAP, LIME)
    • Fairness, bias detection, model risk controls
    • Privacy-preserving ML techniques (differential privacy, federated learning)

  • Programming & Tooling
    • Python, PyTorch, TensorFlow, JAX
    • LangChain, semantic search, vector embeddings
    • Prompt engineering & LLM orchestration frameworks

  • Excellent communication, problem-solving, and project management skills
  • Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
  • Demonstrate company core values of excellence, ownership, collaboration, and integrity.

Preferred
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
  • 5-8 + years of experience in AI/ML or data science.
  • Experience working with large-scale financial or transactional data is preferred.

Credit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.

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