Jobs at XYZ Reality

Own and evolve Azure cloud infrastructure, Kubernetes clusters, Infrastructure-as-Code, CI/CD pipelines, observability, security, reliability, disaster recovery, and developer tooling. Partner with engineering and data teams to support databases, data pipelines, and AI/ML deployments. Improve self-service capabilities, incident response, automation, and production troubleshooting while enabling scalable and secure deployments.

Owns end-to-end recruitment for technology teams, including software engineering, computer vision, BIM/VDC, and product. Partners with hiring leaders on workforce strategy, sources niche global talent, builds pipelines, manages candidate experience, and uses data and market insights to improve hiring outcomes. The role requires hands-on technical recruiting experience in-house or within engineering and deep-tech environments, with proficiency in tools such as Ashby ATS, LinkedIn Recruiter, and GitHub.

Own the ERP replacement and business systems supporting production, quality, procurement, and logistics. Responsibilities include requirements gathering, vendor selection, configuration, data migration, testing, go-live, process mapping, integrations, serial-level traceability, engineering change control, ISO 9001 records, production reporting, and process automation. The role requires manufacturing systems expertise, strong data migration and integration skills, advanced Excel, and the ability to independently deliver large-scale process improvements.

Support on-site delivery by tracking construction progress against BIM models using an AR headset, performing quality inspections, raising and submitting QA issues daily, maintaining data accuracy and reporting, collaborating with site engineers, and supporting the Lead Engineer while receiving mentorship and training.

Deliver on-site AR-enabled construction services: track progress against BIM models using the Atom headset, perform daily quality inspections, raise and submit QA issues via the XYZ platform, maintain data accuracy, and support the Lead Engineer across major construction projects.

Build scalable infrastructure for machine learning training, deployment, monitoring, retraining, and continual learning. Responsibilities include distributed training pipelines, dataset and annotation workflows, experiment tracking, model versioning, benchmarking, CI/CD, cloud-to-edge deployment, inference APIs, and embedded NVIDIA platform optimization. The role collaborates with computer vision, navigation, embedded software, and cloud engineering teams to move AI research into reliable production systems.

Develop advanced 3D computer vision and spatial AI systems for wearable construction technology. Build scene understanding, segmentation, object detection, BIM correspondence, localization, and installation-progress models using multimodal sensor data. Design and train deep learning systems, optimize inference for NVIDIA Jetson using TensorRT, CUDA, and ONNX, and deploy robust production pipelines. Contribute to architecture and R&D strategy while mentoring engineers and collaborating across navigation, embedded software, hardware, and product teams.

Build and own internal business applications, dashboards, automations, integrations, and AI-enabled tools from architecture through deployment and ongoing maintenance. Use TypeScript, React, Next.js, Node.js, and modern serverless platforms to deliver secure, scalable solutions. Collaborate with non-technical stakeholders, implement authentication and data protection, integrate AI and third-party systems, monitor applications, and improve them using feedback and usage data.

The Senior Data Engineer will design and maintain data pipelines using Python, develop efficient SQL queries for API services, collaborate across teams, and optimize system performance, while documenting processes and adapting to new technologies.