Senior Applied Scientist – Cyber Defense

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🧬 Research Scientist

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Partner with security practitioners to identify high-impact workflows and lead delivery of agentic systems for detection, investigation, and response. • Provide technical direction for complex agentic AI initiatives across teams. • Build context-aware agents that analyze security data and institutional knowledge, use approved tools, and support greater autonomy. • Establish repeatable model and agent evaluation using realistic security environments, curated datasets, analyst ground truth, and task-specific benchmarks. • Evaluate end-to-end behavior through automated scoring, trajectory analysis, and adversarial testing. • Improve agent quality, reliability, and efficiency using evaluation results, production traces, and analyst feedback. • Optimize models, retrieval, context, orchestration, and inference against measurable security outcomes. • Take AI capabilities from experimentation to production using software engineering and MLOps/LLMOps practices. • Build continuous evaluation, observability, versioning, controlled deployment, and safe rollback into the lifecycle. • Evaluate NVIDIA, open-source, frontier, and partner AI capabilities using an interoperable, multi-model approach. • Make evidence-based recommendations on adoption, adaptation, development, integration, or co-development. • Translate technical findings into recommendations influencing architecture, Applied AI priorities, and partner roadmaps. • Turn proven approaches into reusable capabilities for NVIDIA’s AI security ecosystem.

🎯 Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Cybersecurity, or a related technical field, or equivalent experience. • 8+ years of relevant experience building and shipping AI, machine learning, or intelligent software systems. • Technical ownership of complex production initiatives. • Strong software engineering skills, particularly in Python. • Experience with TypeScript or C#. • Ability to design reliable and scalable systems beyond prototypes or experimental notebooks. • Hands-on experience with large language models, retrieval-augmented generation, agentic architectures, agent harnesses, or related approaches. • Experience designing AI evaluations and benchmarks using curated datasets, ground truth, task-specific metrics, automated evaluators, error analysis, and expert feedback. • Experience taking AI capabilities through experimentation, deployment, monitoring, optimization, and continuous improvement using MLOps or LLMOps practices. • Demonstrated technical leadership across complex, cross-functional projects. • Ability to exercise independent judgment, influence architecture and technical direction, and drive ambiguous problems to measurable outcomes. • Strong understanding of cybersecurity or experience applying AI and software engineering to security operations, detection, incident response, threat research, or another adversarial domain. • Deep experience with evaluation environments and benchmarks for agentic systems, trajectory-level evaluation, task verifiers, adversarial scenarios, and safety or reliability testing. • Experience designing and calibrating LLM-as-a-Judge or other model-based evaluators. • Experience with agentic architectures, orchestration systems, retrieval and context pipelines, or multi-agent approaches. • Familiarity with NVIDIA AI technologies such as NeMo Evaluator, NeMo Gym, NeMo Agent Toolkit, NVIDIA NIM, Triton Inference Server, RAPIDS, or CUDA. • Recognized contributions through open-source work, benchmarks, publications, patents, conference presentations, or similar AI/cybersecurity contributions.

🏖️ Benefits

• Equity • Benefits