Senior Machine Learning Engineer (Platform)
Core
Build and operate end-to-end ML training, evaluation, and deployment pipelines for engineering-grade digital twins of electricity grids, enabling utilities to simulate extreme weather and optimize infrastructure resilience.
Role type
Senior MLOps Engineer (Platform)
Builds
Production ML pipelines, CI/CD for models, model registries, distributed training infrastructure, and scalable inference services for global utility customers.
Domain
Energy infrastructure / Geospatial data / Digital twins
Deliverable
production ML models
Required skills
Python, PyTorch, distributed training, GPU infrastructure management, cloud platforms (AWS/GCP/Azure), Kubernetes, Docker, infrastructure as code, production model monitoring, data quality frameworks
Preferred skills
CUDA or kernel-level optimisation, point cloud or geospatial data experience, deployments into regulated or air-gapped environments
Technologies
PyTorch, Kubernetes, Docker, AWS, GCP, Azure
Responsibilities
Build and operate ML pipelines from data ingestion to customer deployment; Automate CI/CD for models and reproducible environments; Implement monitoring, alerting, and drift checks for production models; Manage GPU clusters and scheduling across cloud and on-prem environments; Deploy and scale inference services handling spiky load; Improve tooling and workflows for the ML team
Seniority
Senior, hands-on IC
