Description
The role designs, builds, deploys, and scales complex self-running machine learning solutions across computer vision, perception, localization, and related domains. It also automates and optimizes the end-to-end ML model lifecycle through experimental methodology, statistics, coding, MLOps, and production deployment on a GCP-native stack. Responsibilities include developing ML models and algorithms, building scalable pipelines and infrastructure, evaluating and retraining models, deploying systems, and managing model versioning and traceability. The position requires strong Java and Python software engineering, GCP, AI, graph engineering, LLM/agent systems, observability, infrastructure as code, and prior client or industry experience.
