Staff Machine Learning Engineer (Platform), Australia-based, Full Relocation Provided
Core
Own the infrastructure and systems enabling Neara's ML discipline to move fast, ship reliably, and scale without breaking for engineering-grade digital twins of electricity grids.
Role type
Staff Machine Learning Platform Engineer
Builds
Training pipelines, serving architecture, experiment management, and monitoring systems for multi-modal spatial frontier models
Domain
Energy infrastructure + Geospatial AI + Distributed Systems
Deliverable
production ML models
Required skills
ML platform strategy, distributed deep learning systems, training data warehousing, model serving architecture, MLOps, system design, cloud infrastructure, container orchestration, CUDA kernel optimization
Preferred skills
None stated
Technologies
Python, PyTorch, AWS/GCP/Azure, Kubernetes, Docker, CUDA
Responsibilities
Define multi-year technical roadmap for training pipelines and serving architecture; Build foundational tooling to accelerate ML delivery from idea to production; Solve hard distributed systems problems for training across varied GPU hardware; Design scalable serving architecture handling spiky production loads; Unblock the ML team by defining contracts between training, evaluation, and serving
Seniority
Staff, hands-on IC with strategic influence
