Kshitij Mittal
I’m Kshitij Mittal, a generative AI model alignment and red-teaming focused engineer with 3+ years of experience evaluating frontier models for safety, robustness, and failure modes.
About
I’m Kshitij Mittal, a generative AI model alignment and red-teaming focused engineer with 3+ years of experience evaluating frontier models for safety, robustness, and failure modes. I work across RLHF/SFT data curation, adversarial testing (like prompt injection and model stumping), and rigorous benchmark/rubric creation to uncover reasoning and alignment gaps.
I also build hands-on AI systems—ranging from audio/voice digital persona projects with very low latency to code and voice/audio evaluation pipelines using Python, C++, TypeScript, and modern ML tooling. Alongside my R&D work, I’ve led technical roadmaps for digital healthcare systems, combining reliability and compliance thinking with practical software engineering.
- 5 years' experience
- Joined September 2026
Industry experience
- Software & Internet
- Healthcare
- Professional Services
- Computers & Electronics
Work experience· 5 roles
Execute adversarial testing (prompt injection, model stumping) to uncover reasoning errors and safety vulnerabilities. Fine-tune and evaluate state-of-the-art models across text, coding, and voice/audio pipelines, including prosody and acoustic alignment checks. Audit AI-generated Python/C++ code outputs and multi-turn reasoning for logic, time complexity, and safety guardrails. Develop structured scoring rubrics and edge-case benchmark datasets for frontier AI research labs.
Lead the technical roadmap for a digital healthcare platform, including tele-consultation and EMR modules. Coordinate and manage engineering direction while enforcing health data compliance, system reliability, and secure API integrations across healthcare infrastructure.
Evaluate chat models for factual accuracy, safety compliance, and alignment under US guidelines. Engineer complex coding prompts and stress-test LLM solutions for logic, edge cases, and algorithmic complexity.
Education
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