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Generative AI Validation Jobs

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Nurse Scientist
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United States , San Francisco; New York
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221000.00 - 260000.00 USD / Year
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Abridge
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Principal ML & AI Engineer
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United Kingdom
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Dynamic Search Solutions
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Senior Data Scientist - Agentic GenAI
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India , Bengaluru
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Cigres
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Gen AI Python Developer
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India , Pune
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Barclays
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Assistant AI Solution Architecture Manager, Hyperautomation
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India , Bangalore
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Unilever
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Senior Product Manager - AI Workflows (Hedge Funds)
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United States , New York
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177000.00 - 256000.00 USD / Year
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AlphaSense
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Senior Back End Engineer
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Ukraine
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StartupSoft
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Sales Operations Junior Analyst - AI
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Bangladesh , Dhaka
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Optimizely
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Regional AI Commercial Specialist
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United Kingdom , London
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Sabio Group
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SAP S/4HANA Finance Migration Lead
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India , Pune
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Vidushi Infotech SSP Pvt. Ltd.
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Ai/ml engineer
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United States , Rockville
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100000.00 - 140000.00 USD / Year
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Chickasaw Nation Industries, Inc (CNI)
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AI Quality Assurance Intern
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Canada , Toronto
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30.00 - 50.00 USD / Hour
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Cresta
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Customer Success Operations Analyst
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Bangladesh , Dhaka
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Optimizely
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Resourcing Operations Specialist - AI
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Bangladesh , Dhaka
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Optimizely
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Technical Lead
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United Kingdom , London
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AKQA
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Technical Lead
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United Kingdom , London
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AKQA
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Machine Learning Engineer
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Sigma Software Group
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Sales Engineering Lead
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India , Bengaluru
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EvoluteIQ
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Business Consultant
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Italy , Metropolitan City of Bologna
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ARAD Digital
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AI & Analytics Workload Specialist
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India , Bangalore
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Hewlett Packard Enterprise
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Explore the frontier of technology with a career in Generative AI Validation jobs, a critical and rapidly expanding field at the intersection of artificial intelligence, risk management, and ethics. Professionals in this domain act as the essential quality assurance and governance checkpoint for advanced AI systems. Their primary mission is to ensure that generative AI models—such as those creating text, code, images, and audio—are safe, reliable, fair, and effective before and after they are deployed into real-world applications. This is not a development role; it is a role of scrutiny, challenge, and assurance, making it fundamental to the responsible adoption of AI. A Generative AI Validator typically performs a comprehensive, independent review of AI systems throughout their entire lifecycle. Common responsibilities include designing and executing rigorous testing protocols to evaluate a model's performance, accuracy, and robustness. This involves stress-testing the AI under various conditions to identify potential failures, biases, or unexpected behaviors. Validators analyze the model's outputs for fairness, ensuring it does not perpetuate or amplify harmful stereotypes, and they assess its security posture to identify vulnerabilities like data poisoning or adversarial attacks. A significant part of the role is delving into the model's explainability and interpretability, determining whether its decision-making processes can be understood and trusted by humans. They are also responsible for ongoing monitoring of live systems to catch performance degradation or concept drift over time. The culmination of this work is detailed technical documentation and reports that clearly articulate the model's limitations, risk profile, and compliance with both internal standards and external regulations. Validators must then communicate these complex, often technical findings to a diverse array of stakeholders, from the AI developers and data scientists who built the system to senior management and business leaders who rely on its outputs for decision-making. To succeed in Generative AI Validation jobs, individuals need a powerful blend of technical and soft skills. A strong foundation in machine learning and AI concepts is non-negotiable, including a deep understanding of neural networks, transformer architectures, and common generative models like GPT and DALL-E. Proficiency in programming languages such as Python and experience with AI/ML libraries and data analysis tools are standard requirements. Equally important are critical thinking skills, a meticulous attention to detail, and a natural skepticism to effectively challenge assumptions. Strong ethical reasoning is paramount for assessing bias and fairness. Excellent communication skills are crucial for translating technical risks into actionable business insights and for influencing stakeholders. Most positions require an advanced degree in a field like Computer Science, Data Science, Statistics, or Mathematics. For those with a passion for ensuring technology serves humanity safely and ethically, Generative AI Validation jobs offer a challenging, impactful, and highly sought-after career path.

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