This is an individual contributor role blending ML research, applied ML, and software engineering. Topics include trust and safety challenges for large language models (LLMs) and multimodal LLMs (MM-LLMs):
Prompt injection attacks and adversarial robustness
Safety alignment and guardrails
Privacy and confidentiality
(Mechanistic) interpretability
Responsibilities
Designing and executing research experiments on LLM trust and safety
Reading, synthesizing, and producing research papers and technical write-ups
Building, running, and owning systems end-to-end
Contributing to core product capabilities as a founding team member
What We're Looking For
ML & Research
Demonstrated research experience; PhD in a technical field strongly preferred
Ability to identify relevant research questions and find answers through literature review or experimentation
First-author or major contributing authorship on peer-reviewed publications; please list these on your resume or cover letter
Hands-on experience with PyTorch, HuggingFace (Transformers, Datasets), and applied deep learning
Experience training and evaluating deep learning models
Nice to have: LLM fine-tuning, multimodal LLMs, PEFT/LoRA
Nice to have: Familiarity with ML interpretability methods (mechanistic interpretability, sparse autoencoders, linear probes, NLP/Vision interpretability)
Software Engineering
Proficiency in Python; experience with Jupyter notebooks
Unix environments, Git, and basic AWS/GCP usage
Nice to have: Programming languages well-roundedness; experience with statically-typed and functional programming languages
Nice to have: Familiarity with (LLM) deployment tooling like Docker, vLLM, Triton Inference Server or similar
Logistics
Available to start within 2 months
Role may include limited on-call responsibilities tied to production ownership
Additional Information
This is a founding, high-ownership role with direct impact on core product capabilities.
You will be expected to build, run, and own systems end-to-end.
The role may include limited on-call responsibilities aligned with production ownership.
About RealmLabs
AI systems misbehave: they leak sensitive data, get manipulated through prompt injections, or behave in ways their builders never intended. RealmLabs is building the infrastructure to detect, debug, and prevent these behaviors.
Our approach is to secure AI from within: observing models from the inside, extracting signals relevant to their behavior and misbehavior, and patching them on the inside, rather than relying on input/output filters or external guardrails.
We are a pre-seed startup and a finalist in the RSAC 2026 Innovation Sandbox. Our customers include Anthropic, a leading ride-sharing platform, and a Big 3 management consulting firm.
This is a founding engineer role with meaningful equity at an early-stage company.
Compensation & Benefits
Market aligned compensation and benefits.
Founding equity (Equity is a significant component of this role and will be discussed)
Medical, Dental, Vision, Life insurance, 401-K, In-office lunch etc.
Visa sponsorship
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and candidate. But if we make you an offer, we will make all reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
Numbers & Facts
Location
Sunnyvale, California
Skills
Amazon Web Services (AWS)unmatched
Artificial Intelligence (AI)unmatched
Computer Securityunmatched
Debugging Skillsunmatched
Dockerunmatched
Functional Programming Languagesunmatched
GCP (Good Clinical Practices)unmatched
Gitunmatched
Injectionsunmatched
Input/Outputunmatched
Insuranceunmatched
Management Consultingunmatched
Natural Language Processing (NLP)unmatched
On Callunmatched
Programming Languagesunmatched
Publicationsunmatched
Python Programming/Scripting Languageunmatched
Software Engineeringunmatched
Software Patchesunmatched
Startupunmatched
Technical Researchunmatched
Unix Operating Systemsunmatched
Writing Skillsunmatched
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