AI Platform Engineer, Training and 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. Customers trust Saviynt to safeguard their digital assets, drive operational efficiency, and reduce compliance costs. 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.

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. Customers trust Saviynt to safeguard their digital assets, drive operational efficiency, and reduce compliance costs. 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.

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. Training & Inference is the engine — it turns data into deployed models that make Saviynt's products smarter.

What You Will Be Doing

Own the Ray ecosystem end-to-end

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

Operate distributed training with Ray Train

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

• Build and operate the LLM inference mesh with Ray Serve: compose vLLM (PagedAttention), SGLang (RadixAttention), and NVIDIA Triton (TensorRT/ONNX) as a unified deployment graph with Plasma zero-copy memory sharing

Optimise inference performance

configure fractional GPU allocation, enable continuous batching, implement per-engine autoscaling based on request queue depth, and tune KV-cache block sizes

Design and operate the model routing layer

capability-based, version-based, and tenant-based routing with cost-aware fallback between self-hosted SLMs and cloud LLMs

Build RL training infrastructure

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

Operate the full model promotion lifecycle

quality gate → integration tests → load tests (k6) → shadow mode → A/B gate → canary (10%→100%) with golden-signal auto-rollback

Operate the retrain pipeline

drift detection triggers, warm-start retraining, relative quality gates (V2 >= V1 − 2%), and automated Flyte DAG through to canary

Integrate RAG retrieval into the inference mesh

vector similarity search, context assembly, and prompt construction before LLM inference

What You Bring

• Experience in ML engineering with time in an ML platform or MLOps role

Production Ray depth

Ray Train, Serve, Core, and Data — debugged real production failures including NCCL timeouts, Plasma OOM, and Serve autoscaling lag

LLM serving engines

hands-on with vLLM, SGLang, or NVIDIA Triton — PagedAttention, prefix caching, and continuous batching tuned for latency/throughput targets

Distributed training

DDP, FSDP, NCCL collectives, gradient checkpointing, and mixed precision (BF16/FP8)

RL working knowledge

PPO, policy gradient, or RLHF — able to translate an algorithm into distributed compute primitives

Model lifecycle operations

MLflow registry, shadow/A/B/canary patterns, and auto-

rollback on golden signal degradation

Vector databases

Pgvector or Qdrant — ANN index strategies, embedding upsert, and query latency tuning under inference load

• Strong Python and PyTorch; Flyte or equivalent ML orchestrator

Quantization (nice to have)

INT8/INT4/FP8 post-training quantization (GPTQ, AWQ, or bitsandbytes)

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent

practical experience or equivalent military experience

We offer you a competitive total rewards package, learning and tremendous opportunities to grow and advance in your career. 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 training; licensure and certifications; and other relevant business and organizational needs.

You may also be eligible to participate in a Saviynt discretionary bonus plan, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Saviynt is an amazing place to work. We are a high-growth, Platform as a Service company focused on Identity Authority to power and protect the world at work. You will experience tremendous growth and learning opportunities through challenging yet rewarding work which directly impacts our customers, all within a welcoming and positive work environment. If you're resilient and enjoy working in a dynamic environment you belong with us!

Security & Compliance

This role requires adherence to Saviynt’s information security and privacy policies and procedures, including annual security training.

Saviynt is an equal opportunity employer and we welcome everyone to our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.