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Senior Machine Learning Engineer

Greenroom Robotics
Sydney NSW

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Job Details

Qualifications

Computer vision
Docker
Terrafrom
Agile
Robotics
Communication skills
Software architecture

Full Job Description

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

Nice to Have

Maritime or robotics domain experience

Why Greenroom?

Work on cutting-edge autonomy software for real-world maritime applications

Work with intelligent and driven engineers who care about the impact they have on the world

Direct impact through systems deployed in the field around the world

Make a difference by reducing whale strikes and improving the safety of offshore operations

Collaborative team that values learning and cross-disciplinary problem-solving

Offices in Sydney and Perth

Dog friendly office (for friendly doggos)

Well stocked pantry suitable for coffee snobs

Competitive salary, dependent on experience

How to Apply

Email us at [email protected]

Apply Now

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