Software Engineer - Machine Learning

3+ years of industry experience in ML engineering or applied AI research

, with demonstrated ownership of production ML systems

2+ years of industry experience in software engineering post-master's degree graduation.

(or JAX/TensorFlow), with solid software engineering fundamentals (version control, testing, and reproducible experimentation).

for safety, content moderation, abuse detection, or adversarial robustness.

Familiarity with prompt injection, jailbreak, and agentic AI threat models, and with distributed training frameworks (DeepSpeed, FSDP, Accelerate).

$95 - 110/hr

**No C2C resumes are considered**

Design and train prompt-injection detection models and prompt-safety classifiers that operate on both inputs to and outputs from the client's agentic AI systems.

Build hybrid deployment pipelines that split safety inference between on-device (phone, XR/AR) and cloud, optimizing for latency, privacy, and detection coverage.

Curate and generate adversarial training data: direct and indirect prompt injections, jailbreaks, tool-use exploits, and unsafe-output cases drawn from red-teaming and production signals.

Build evaluation harnesses that measure attack success rate, false-positive rate, latency, and on-device footprint across model iterations and threat categories.

Partner with agent, device, and platform teams to integrate safety models into mobile-use agents, XR/AR assistants, and cloud agentic workflows, and to close the loop from production incidents back into training data.

Work cross-functionally with security researchers, modeling teams, and product engineers; document methods and, where appropriate, contribute to patents and publications.