Saviynt
AI Platform Engineer, Training and Inference
Milpitas, California
Sponsorship not specified$274k-$304kDetected 64 days ago
PythonNode.jsPlatform EngineeringMachine LearningPyTorchLLMsMLOps
About the role
- Built for the AI age, Saviynt is today helping organizations safely accelerate their deployment and usage of AI.
- Saviynt is recognized as the leader in identity security, with solutions that protect and empower the world's leading brands, Fortune 500 companies and government institutions.
- For more information, please visit www.saviynt.com.
Responsibilities
- AI Platform Engineer - Training & Inference Saviynt's AI-powered identity platform manages and governs human and non-human access to all of an organization's applications, data, and business processes.
- manage KubeRay on GKE, tune Ray Core Task/Actor scheduling, operate the Plasma distributed object store, and configure Ray Data for GPU-direct streaming from GCS/S3
- configure TorchTrainer + DDP/NCCL for multi-node H100 clusters, manage checkpoint lifecycle, implement spot-preemption recovery, and integrate warm-start fine-tuning for retrain pipelines
- configure fractional GPU allocation, enable continuous batching, implement per-engine autoscaling based on request queue depth, and tune KV-cache block sizes
- define Flyte workflows for RL pipelines (rollout, reward shaping, policy update, evaluation), integrate Ray RLlib or custom PPO/GRPO loops with Ray Train, and manage replay buffer persistence on GCS
Requirements
- Experience in ML engineering with time in an ML platform or MLOps role
Nice to have
- experience and training
- licensure and certifications
- and other relevant business and organizational needs.
Skills
- capability-based, version-based, and tenant-based routing with cost-aware fallback between self-hosted SLMs and cloud LLMs
- Strong Python and PyTorch; Flyte or equivalent ML orchestrator
Compensation
- At Saviynt, it is not typical for an individual to be hired at or near the top of the range for their role and final compensation decisions are dependent on many factors including, but not limited to location; skill sets; experience and tra
Company info
- Customers trust Saviynt to safeguard their digital assets, drive operational efficiency, and reduce compliance costs.
- The AI Platform team is building the compute layer that trains, evaluates, and serves every AI model at Saviynt.
- We need an ML Platform Engineer to own distributed training on Ray + H100s, the multi-engine LLM inference mesh (vLLM, SGLang, NVIDIA Triton), and the full model promotion lifecycle - from shadow mode through canary rollout to GA.
- The AI Platform team's mission is to build a secure, scalable, product-agnostic AI foundation that enables Saviynt's identity products to deliver measurable AI-powered outcomes.
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This listing is sourced directly from Saviynt's careers page and normalized into a canonical job model.