About Greenroom Robotics

At Greenroom Robotics, we're revolutionizing maritime operations through cutting-edge Robotics, Autonomous Systems, and Artificial Intelligence. As Australia's leading Maritime Autonomous Systems provider, we deliver high-performance solutions to complex real-world problems with teams spread across Australia working on global projects.

About the Role

We're seeking a Senior Machine Learning Engineer to own the machine learning, data, and deployment pipelines behind Lookout+, our perception system that flows into GAMA to detect, classify, track, and avoid hazards at sea.

This is a hands-on, build-focused role spanning deep learning, computer vision, and the data and deployment pipelines that take models from prototype to production on edge hardware operating on real vessels around the world. Reporting to our Perception Lead and working alongside the Principal Software Architect and CTO, you'll take end-to-end ownership of our ML frameworks, from research and prototyping through to production deployment.

Key Responsibilities

Own the design and implementation of end-to-end ML pipelines and computer vision solutions for Greenroom products
Design and deploy production-grade ML models for maritime perception: vessel detection, tracking, classification, and semantic segmentation
Develop computer vision pipelines using modern architectures optimized for real-time edge deployment
Build and manage data pipelines for large volumes of maritime vision data, including ingest, labeling, dataset construction, and usage-rights tracking
Build scalable training infrastructure and MLOps workflows with experiment tracking, monitoring, and continuous model improvement
Scale training and deployment infrastructure to the cloud using infrastructure-as-code (Terraform, Kubernetes)
Optimize neural networks for NVIDIA edge hardware (Jetson) using techniques such as quantization and pruning for low-latency execution
Develop prototypes and proof-of-concepts demonstrating new ML-driven capabilities
Establish ML engineering best practices and production deployment workflows with the Perception Lead, Principal Software Architect, and CTO

Required Skills

Technical Expertise

Strong proficiency in Python (C++ advantageous)
Computer vision and deep learning, with a track record of production ML
Object detection, tracking, classification, and semantic segmentation
Machine learning and data science: dataset construction and running experiments
Edge deployment and model optimization: NVIDIA Jetson, TensorRT, DeepStream, ONNX, quantization, and pruning

MLOps & Data Engineering

Building and maintaining ML pipelines from data collection to deployment
MLOps, training infrastructure, and experiment tracking (e.g. MLflow)
Data engineering and cloud infrastructure: large-scale data management and cloud scaling (Terraform, Kubernetes)
Containerization (Docker) and orchestration tools

Personal Qualities

Strong problem-solving skills and the ability to work in dynamic environments
Experience in agile development
Excellent communication skills for cross-functional collaboration
Passion for autonomous systems, the ocean, and cutting-edge technology

Responsibilities