Principal Engineer, AI Platform & Infrastructure

SPREEAI is a fast-growing, innovative AI company at the forefront of fashion and e-commerce, revolutionizing how consumers engage with fashion through lifelike photorealistic try-on technology and hyper-personalized shopping experiences. The Principal Engineer will build the infrastructure, deployment pipelines, and observability systems for multimodal AI models, enabling reliable production-grade deployments for real-time virtual try-on experiences.

Responsibilities:

• Build and operate SPREEAI’s end-to-end ML platform spanning training, evaluation, deployment, and monitoring
• Enable scalable and reliable training workflows through orchestration, infrastructure, and resource management systems
• Define platform standards for model packaging, model registry, dataset lineage, experiment tracking, checkpointing, and deployment automation
• Enable reliable and scalable inference deployments through standardized serving, orchestration, and monitoring frameworks
• Build and operate model deployment pipelines with versioning, reproducibility, rollback, approval gates, evaluation gates, and production observability
• Establish production SLOs for latency, availability, error rate, GPU saturation, cold-start time, cost per inference, and model quality drift
• Standardize and support serving infrastructure using modern inference runtimes such as vLLM, NVIDIA Triton, TensorRT-LLM, Ray Serve, TorchServe, ONNX Runtime, or equivalent systems
• Design and manage GPU allocation, scheduling, and resource utilization across training and inference workloads
• Improve GPU utilization, throughput, latency, reliability, and cost efficiency across model lifecycle systems
• Design and operate model evaluation and benchmarking systems, including automated regression detection and quality gates for production releases
• Partner with research teams to productionize new capabilities by providing robust infrastructure, tooling, and deployment pathways