DeepKeep
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About
DeepKeep is a model-agnostic, multi-layer platform providing AI-native security and trustworthiness for AI applications. It continuously identifies vulnerabilities throughout the AI lifecycle, offering automated security and trust remedies. Built using GenAI, DeepKeep secures various modalities, including LLM, vision, and tabular data, addressing adversarial attacks, cyberattacks, risk exposures, regulatory compliance, and overall trust. The platform offers continuous risk assessment, an AI firewall, and holistic security and trust protection. DeepKeep serves large corporates in finance, security, automotive, and AI computing sectors.
Platform
Task
Features
• ai firewall
• continuous risk assessment
• protecting multimodal including llm, image and tabular data
• security and trustworthiness for holistic protection
• real-time detection, protection and inference
• protection, monitoring, and mitigation
• risk assessment and confidence evaluation
• ai-native security
Job Opportunities
Team Leader ML Engineer
DeepKeep provides AI-native security and trust for AI applications by continuously identifying and addressing vulnerabilities throughout the AI lifecycle.
Education Requirements:
Master's degree in Computer Science, Mathematics, or a related field
Experience Requirements:
Minimum 6 years of development experience, with at least two years as a machine learning engineer
Other Requirements:
Exceptional Python coding skills
Proficiency in machine learning frameworks (e.g., PyTorch, TensorFlow)
Expertise in specialized machine learning databases
Hands-on experience in MLOps
Responsibilities:
Lead the translation of advanced research prototypes into scalable, production-grade software
Optimize the utilization of machine learning models
Collaborate closely with data scientists
Design and implement efficient machine learning systems
Drive ambitious projects through collaboration with cross-functional teams
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Senior Computer Vision Researcher
DeepKeep provides AI-native security and trust for AI applications by continuously identifying and addressing vulnerabilities throughout the AI lifecycle.
Education Requirements:
Master's degree in Computer Science, Mathematics, or a related field
Experience Requirements:
3+ years of experience working with computer vision models
Other Requirements:
Proficiency in Python and experience with deep learning frameworks like PyTorch
Generative experience
Publications or contributions to the adversarial or computer vision AI community
Responsibilities:
Develop state-of-the-art models and techniques
Conduct research on adversarial attack and defense techniques
Collaborate with team members
Help with the research and development of new generative vision pipelines
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Manual QA Engineer
DeepKeep provides AI-native security and trust for AI applications by continuously identifying and addressing vulnerabilities throughout the AI lifecycle.
Experience Requirements:
Minimum of 3 years of experience in manual QA or related fields
Other Requirements:
Experience in identifying and documenting bugs
Experience in testing web applications
Excellent problem-solving and critical thinking skills
Responsibilities:
Manually test front-end and back-end systems
Collaborate with the product team and team leader
Identify and document defects
Perform regression testing
Contribute to product design reviews
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