DeepKeep
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About
DeepKeep is an AI-Native Security platform that safeguards AI Applications. It identifies seen, unseen & unpredictable AI / LLM vulnerabilities throughout the AI lifecycle with automated security & trust remedies. DeepKeep empowers large corporates that rely on AI, GenAI and LLM to manage risk and protect growth with AI-Native Security and Trust. It offers continuous risk assessment, AI firewall, and AI-native features enabling data scientists, ML engineers, compliance and CISO teams to gain valuable insights into the risks and challenges of AI.
Platform
Task
Features
• ai firewall
• continuous risk assessment
• protecting multimodal including llm, image and tabular data
• ai-native security
• physical sources beyond the digital surface area
• exposure within and across models throughout ai pipelines
• realtime detection, protection and inference
• ai-native security and trustworthiness
Job Opportunities
Team Leader ML Engineer
DeepKeep is a Generative AI built platform that continuously identifies seen, unseen & unpredictable AI / LLM vulnerabilities throughout the AI lifecycle with automated security & trust remedies.
Experience Requirements:
Minimum 6 years of development experience, with at least two years as a machine learning engineer.
Responsibilities:
Lead the translation of advanced research prototypes into scalable, production-grade software.
Optimize the utilization of machine learning models, implementing techniques such as early stopping and optimization against adversarial attacks.
Collaborate closely with data scientists to understand research findings and translate them into practical, scalable solutions.
Design and implement efficient machine learning systems compatible with diverse data types and integrable with technologies like transformers.
Drive ambitious projects through collaboration with cross-functional teams, ensuring seamless integration of machine learning technologies across our product suite.
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Senior Computer Vision Researcher
DeepKeep is a Generative AI built platform that continuously identifies seen, unseen & unpredictable AI / LLM vulnerabilities throughout the AI lifecycle with automated security & trust remedies.
Education Requirements:
Completed a Master's degree in Computer Science, Mathematics, or a related field, with a published paper in a respectable journal or conference.
Experience Requirements:
at least 3 years of experience working with computer vision models.
Responsibilities:
Develop your SOTA: Our team is a pioneer in adversarial AI research with numerous studies under our belt. We will guide your research, development, and implementation of state-of-the-art (SOTA) models and techniques.
Research and Development: Conduct research on adversarial attack and defense techniques for computer vision models. Explore state-of-the-art methods and propose innovative solutions.
Collaboration: Work closely with team members, participate in brainstorming sessions, and contribute to the team's success.
Generative Vision: You will help with the research and development of new generative vision pipelines, tackling various modalities and challenges.
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Manual QA Engineer
DeepKeep is a Generative AI built platform that continuously identifies seen, unseen & unpredictable AI / LLM vulnerabilities throughout the AI lifecycle with automated security & trust remedies.
Experience Requirements:
Minimum of 3 years of experience in manual QA or related fields.
Experience in identifying and documenting bugs, testing web applications, and working with development teams.
Responsibilities:
Manually test front-end and back-end systems to ensure functionality, performance, and reliability.
Collaborate daily with the product team and team leader to review, prioritize, and address reported bugs and system issues.
Identify and document defects, working with developers to ensure timely resolution.
Perform regression testing to validate that resolved issues remain fixed.
Contribute to product design reviews by providing input on potential user experience issues or risks.
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