Senior Machine Learning Engineer (Platform)

Role overview

What you’ll do

• Own training, evaluation and deployment pipelines from data ingestion through models running in customer environments.
• Build CI/CD, artifact and model registries, reproducible environments and infrastructure as code for automated production delivery.
• Implement monitoring, alerting, drift detection and data quality checks, and respond to production failures.
• Manage GPU clusters and scheduling across cloud, on-premise and neocloud environments while improving utilization.
• Deploy and scale inference services across regions and customers with attention to latency, cost and data residency.
• Improve ML engineering tools and workflows and document standards as the team grows.

What you’ll bring

• Hands-on experience operating ML training pipelines, model serving and monitoring systems in production.
• Strong Python and working knowledge of PyTorch or an equivalent framework.
• Experience with distributed training and GPU infrastructure, including scheduling, resource management and performance troubleshooting.
• Experience with AWS, GCP or Azure, Kubernetes or Docker, and infrastructure as code.
• Experience with production model monitoring, data quality frameworks and ML-ready training data.
• Sound engineering judgment, maintainable coding practices and consideration of failure modes.

Bonus experience

• CUDA or kernel-level optimization experience.
• Exposure to point cloud or geospatial data.
• Experience supporting deployments into regulated or air-gapped customer environments.

Work environment

• Neara describes a fully flexible work environment and maintains a stocked office in Redfern.
• The posting does not specify whether the role is remote, hybrid or office-based.

Benefits

• The package includes competitive salary, meaningful ESOP and regular office events.
• Neara emphasizes work on a complex product intended to improve climate resilience for critical infrastructure.

About Neara