Senior Applied AI Scientist
Posted 22 days ago · 0 applicants
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The role in plain words
- 5 years of hands-on ML and deep learning experience
- track record of shipping, debugging, and diagnosing models in production
- Data-first mindset: you know how to define the right evaluation criteria for each model - before and after shipping, to ensure it delivers real quality and value in production
- Hands-on experience building and deploying agentic AI systems to production
- Proficiency in Python
- Background in security, trust & safety, or content moderation
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Who this suits
Full job description
Original listing · kept for referenceAbout Us: Zenity is the first and only holistic platform built to secure and govern AI Agents from buildtime to runtime. We help organizations defend against security threats, meet compliance, and drive business productivity. Trusted by many of the world’s F500 companies, Zenity provides centralized visibility, vulnerability assessments, and governance by continuously scanning business-led development environments. We recently raised $38 million in a Series B funding, solidifying our position as a leader in the industry and enabling us to accelerate our mission of securing AI Agents everywhere. About the Job: We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies. You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.
Requirements: • 5 years of hands-on ML and deep learning experience, with a track record of shipping, debugging, and diagnosing models in production • Data-first mindset: you know how to define the right evaluation criteria for each model - before and after shipping, to ensure it delivers real quality and value in production • Hands-on experience building and deploying agentic AI systems to production • Proficiency in Python; experience with PyTorch, scikit-learn, HuggingFace, or equivalent • Practical, applied mindset - focused on the problem, success metrics and impact, not lab research. • • Background in security, trust & safety, or content moderation - an advantage
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 5 years of hands-on ML and deep learning experience, track record of shipping, debugging, and diagnosing models in production, Data-first mindset: you know how to define the right evaluation criteria for each model - before and after shipping, to ensure it delivers real quality and value in production, Hands-on experience building and deploying agentic AI systems to production, Proficiency in Python