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About the Role
Neara uses advanced machine learning to create digital twins of electricity grids, simulating extreme weather and structural stress to help utilities optimize investments and build a more resilient global energy future. The Staff Machine Learning Platform Engineer will own the infrastructure and systems enabling the ML discipline to move fast, ship reliably, and scale effectively.
Responsibilities
- Own the ML platform strategy end-to-end, defining and driving the technical roadmap for training pipelines, serving architecture, experiment management, and monitoring systems.
- Build tooling to accelerate ML delivery, developing foundational infrastructure to streamline the process from idea to production.
- Solve complex distributed systems problems to enable distributed data training with residency and security requirements, ensuring efficient model execution across varied GPU hardware.
- Design scalable and flexible serving architecture to handle spiky production loads while allowing ML team experimentation.
- Unblock the ML team at scale by identifying bottlenecks, defining interfaces between training, evaluation, and serving, and building roadmaps for research implementation.
Requirements
- Significant hands-on experience building and operating training pipelines, distributed compute, model serving, and monitoring systems at scale.
- Strong proficiency writing and optimizing custom CUDA kernels for deep learning training, ideally across non-text/image data types, with experience diagnosing performance bottlenecks in sparse architectures.
- Proven experience with production model monitoring, data quality frameworks, and training data warehouses brought to ML readiness.
- Demonstrated ability to set ML platform standards, influence engineering roadmaps, and drive alignment on complex infrastructure decisions across teams without direct authority.
- Proficiency in Python and PyTorch (or equivalent), strong system design instincts, and an R&D foundation.
- Experience with AWS, GCP, or Azure, container orchestration (Kubernetes, Docker), and on-prem or neocloud environments.
- A track record of leading, mentoring, and coaching ML engineers, raising the technical bar of teams through guidance, documentation, and internal standards.
Skills
- Machine Learning
- Python
- PyTorch
- CUDA
- Distributed Systems
- System Design
- AWS
- GCP
- Azure
- Kubernetes
- Docker
- MLOps
Location
- Redfern
Work Type
- Fully Flexible Work Environment
Experience Level
- Staff
Salary/Compensations
- Competitive salary
Benefits
- Meaningful ESOP
- Fully stocked office
- Impressive snack collection
- Regular office events
About the Company
- Neara uses advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents.
- We help asset owners understand their biggest challenges and bring the most viable solutions to life across millions of kilometres of infrastructure.
- By simulating extreme weather and structural stress at a network-wide scale, we empower the world’s largest utilities to pinpoint risks, optimise investments and build a more resilient global energy future.
- Our team is a collection of brilliant minds who are fanatical about making a tangible difference in the real world, utilising AI and machine learning to accelerate everything from data classification to complex scenario analysis.
- We have built a special culture where innovation thrives because everyone owns the mission.
Equal Opportunity
- Neara values diversity, belonging and equal employment opportunities. We encourage individuals from all backgrounds to apply.