> Markdown version of [/jobs/ext/1469213-evaluation-and-ml-systems-engineer-ai-safety-and-security-engineering](https://www.wearedevelopers.com/jobs/ext/1469213-evaluation-and-ml-systems-engineer-ai-safety-and-security-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Evaluation and ML Systems Engineer, AI Safety and Security Engineering - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $152,000.0 - $241,500.0 - **Contract:** Permanent contract - **Skills:** Python (Programming Language), Machine Learning, Software Safety, Large Language Models, Multi-Agent Systems, Machine Learning Operations, Data Pipelines - **Published:** July 28, 2026 - **Apply:** https://www.disabledperson.com/jobs/73888201-evaluation-and-ml-systems-engineer-ai-safety-and-security-engineering ## About the Role * Bachelor's degree (or equivalent experience) with 5+ years in ML engineering or evaluation. * Evaluation experience: Designing benchmarks, metrics, and statistically sound comparisons for ML systems. * Measurement rigor: A careful, skeptical approach to metrics, baselines, and claims. * Engineering skills: Solid Python engineering for shared infrastructure, including experiment tracking and data pipelines. Ways to Stand Out from the Crowd: * Security evaluation: Exposure to evaluating security tooling or pipelines. * Agentic systems: Experience measuring agent or LLM behavior. * Community work: Contributions to public benchmarks or evaluation frameworks. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Psychological Safety in Software Engineering - Jenny-Margrethe Vej & Alexandra Hou Aldershaab](https://www.wearedevelopers.com/videos/2142-psychological-safety-in-software-engineering-jenny-margrethe-vej-alexandra-hou-aldershaab) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction)