Senior MLOps Engineer

Role overview

Build the systems that move machine learning models from development into reliable production use. The work spans training pipelines, model releases, browser-ready inference, and GPU-backed processing for identity and age verification.

Responsibilities - Develop and maintain training pipelines for age classification and face recognition models. - Create model versioning and release processes that support multiple classifiers and recognition models. - Automate conversion and deployment of models in ONNX format for client-side inference. - Orchestrate GPU workers for image and document processing tasks such as OCR. - Partner with machine learning researchers and engineers to make models production-ready.

Requirements - Demonstrated experience building and operating machine learning infrastructure in production. - Ability to design dependable training, evaluation, and deployment pipelines. - Experience managing model versions and automating model packaging or release workflows. - Familiarity with deploying models for inference across different execution environments.

Benefits and work setup - Full-time, remote role open to candidates in the US or Europe. - Listed compensation range: $160,000–$210,000.