Rubrik
Senior Machine Learning Engineer
Palo Alto, CA · Senior
Sponsorship not specified$189k-$283kDetected 7 days ago
PythonAzureCloud PlatformsMachine LearningDeep LearningPyTorchData EngineeringLLMsAgentic AIStatisticsCybersecurityAuditingResearchLeadershipCollaborationMentoring
About the role
- SAGE powers Rubrik Agent Cloud: enterprises define governance policies in natural language, and SAGE's custom small language models act as judges on every agent action.
- At its core, SAGE is "LLM-as-judge" applied to AI governance, utilizing the same technique most teams use for offline evaluation but productionized for real-time enforcement at enterprise scale.
- Our first-generation SLM Policy Guard already outperforms the larger frontier models we've benchmarked against on accuracy while running approximately 5x faster on the same workload.
Nice to have
- Deep background in AI safety and red-teaming, including hands-on experience with adversarial ML, prompt injection defense strategies, and automated evaluation suites for enterprise-grade LLM safety.
- Experience with context-fusion and retrieval systems that synthesize disparate signals - such as data sensitivity, user identity, and behavioral history - into high-fidelity model decisions.
- Production experience with low-latency inference for streaming or safety-critical request paths where model throughput and P99 SLOs are paramount.
- Hands-on knowledge distillation experience, successfully transferring capabilities from frontier teacher models to specialized, small-scale student models for production serving.
- Familiarity with the agentic ecosystem, including tool-use frameworks, model gateway architectures (MCP, LiteLLM, or equivalent), and autonomous agent patterns.
- Active open-source contributions to mainstream ML training, serving, or evaluation libraries.
- The minimum and maximum base salaries for this role are posted below
- Join Us in Securing and Accelerating the World's AI Transformation
Skills
- enterprises define governance policies in natural language, and SAGE's custom small language models act as judges on every agent action.
- As an Applied
Compensation
- Within the range, the salary offered will be determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
This listing is sourced directly from Rubrik's careers page and normalized into a canonical job model.