Senior Machine Learning Engineer (Platform)

About Neara

At Neara, we're revolutionizing the energy sector by using state-of-the-art machine learning to develop engineering-grade, physics-enabled digital twins of electricity grids spanning four continents. Our technology equips asset owners with the insights to tackle their toughest challenges by simulating extreme weather events and structural stress over vast infrastructure networks. Through this, we enable the world's largest utilities to identify risks, optimize capital allocation, and build a resilient energy future globally.

Role Overview

We are seeking a Senior MLOps Engineer to design, operate, and maintain comprehensive ML pipelines, deployment systems, and monitoring solutions that ensure Neara's machine learning models are robustly trained and reliably served in production environments. This role supports cutting-edge research into multi-modal spatial frontier models involving diverse and less-explored data types, such as point clouds, geospatial, and asset datasets. The position requires navigating unique challenges in performance, data integration, and deployment for geospatial AI applications.

Key Responsibilities

• Develop and manage end-to-end ML pipelines that cover data ingestion, model training, evaluation, and deployment into customer environments.
• Automate the transition from model experimentation to production by implementing continuous integration and continuous deployment (CI/CD) pipelines, model/artifact registries, reproducible environments, and infrastructure as code.
• Maintain operational health of production models through monitoring, alerting, drift detection, and data quality assessments, promptly addressing any disruptions.
• Oversee distributed training infrastructure involving GPU clusters, including job scheduling, utilization efficiency, and troubleshooting failures across cloud, on-premises, and Neara's proprietary neocloud platforms.
• Deploy and scale reliable inference services optimized for latency, cost efficiency, and compliance with data residency across regions and customer bases.
• Enhance ML engineering productivity by refining tooling, workflows, and documenting standards to maintain consistency as the team expands.

Required Qualifications and Skills

• Proven hands-on experience in building and maintaining ML training pipelines, model serving systems, and monitoring mechanisms in live production settings.
• Strong expertise in Python programming and practical knowledge of PyTorch or similar frameworks, adequate to debug training workflows.
• Experience managing distributed training environments and GPU resources, including scheduling, resource allocation, and resolving performance or memory bottlenecks.
• Familiarity with cloud service providers such as AWS, GCP, or Azure, container orchestration technology (Kubernetes, Docker), and infrastructure as code practices.
• Competence in production-level model monitoring, data quality frameworks, and preparing datasets for machine learning use.
• Excellent software engineering judgment, with an emphasis on writing maintainable code, anticipating failure scenarios, and balancing quick fixes with long-term solutions.
• Bonus: Knowledge in CUDA programming or kernel-level optimization, working with point cloud or geospatial data, or experience in deploying systems within regulated or air-gapped environments.

Compensation & Benefits

• Attractive salary package
• Significant employee stock ownership plan (ESOP)
• Flexible working arrangements supported by a fully stocked, modern office in Redfern, including a wide assortment of snacks
• Regular social and team-building events
• Opportunity to contribute to a sophisticated, groundbreaking product that positively impacts global infrastructure resilience in the face of climate challenges

Additional Information

Neara champions diversity, inclusion, and equal employment opportunities, encouraging applicants from all backgrounds to join us. Agencies and third-party service providers are kindly requested not to apply.