What We Do
Position Summary
What You’ll Deliver
Required Skills
Preferred Expertise
What you are joining
About Us
At Unleash live, we don’t just follow trends—we set them. We are a world-leading AI video analytics platform transforming high-velocity visual data into real-time, actionable insights for the world’s most critical industries. From autonomous drone inspections to real-time traffic optimization, we operate at the frontier of what’s possible. We are looking for an engineer energized by turning experimental technology into enterprise-grade reality—whether in the cloud or on a remote sensor in the field.
You will join our high-octane MLOps Team, the architectural heart of our AI ecosystem and the bridge between digital intelligence and physical reality. We manage enabling the entire model lifecycle—from training and optimization to large-scale deployment. We build ecosystems that allow models to thrive in the wild, ensuring our intelligence is always accurate, always on, and ahead of the curve.
This role is for a versatile builder at the intersection of Machine Learning Operations, Data Architecture, and Edge Integration. You will support the deployment strategies powering our global platform to ensure seamless performance.
We seek an engineer with a genuine passion for Computer Vision. You understand the unique infrastructure challenges of visual data—latency, frame-rate consistency, and processing high-volume streams under compute constraints.
Core Engineering Skills
Software Design Patterns: Production-grade code for system orchestration in Node.js (Backend) and Angular (Frontend).
Cloud Proficiency: Experience with AWS (SageMaker, Bedrock, Greengrass, etc.) to manage high-volume AI workflows at scale.
Linux & Containers: Experience with containerization (Docker); ability to orchestrate is a nice-to-have.
Database Fluency: Understanding of DynamoDB is sufficient.
Data Focus: Experience with Databricks (Unity Catalog, Delta Lake), expert-level Data Modeling, and distributed computing (Apache Spark).
Edge & IoT Focus: Hands-on experience with hardware (NVIDIA Jetson/Orin, Raspberry Pi), Hardware Prototyping (electronics/circuit troubleshooting), and IoT protocols (MQTT, RTSP/WebRTC, I2C).
When you join us, you aren't just taking a job; you are joining a culture defined by:
Inquisitive & Bold Innovation: We are naturally drawn to the bleeding edge and are constantly looking for ways to bring new efficiencies to our stack.
A "Field" & "Owner" Mindset: We enjoy the hard challenges and take pride in building systems that excel; when we see a bottleneck, we fix it.
Architectural Excellence: We look at the big picture, designing elegant and scalable systems for the scale of tomorrow, not just the bugs of today.
Flexible & Social Culture: We offer flexible work arrangements that respect your life outside of work, balanced with frequent social events to keep us connected.
Own Your Growth: Be the master of your own professional evolution; we prize technical leadership and provide the full support and mentorship needed to reach your peak.
Unleash live is a leading Australian-born deep tech company transforming how the world’s most critical industries interact with data. We specialise in cutting-edge computer vision, turning live visual data into immediate, actionable insights across the globe.
By operating at the intersection of AI and autonomy, our platform enables enterprises and governments to monitor and optimize infrastructure with unprecedented precision. From bushfire detection to energy grid resilience, we help machines not just capture the world, but understand it.
Our diverse team of "thinkers and tinkerers" is driven by a shared obsession: solving hard problems with impactful technology. Whether you are seeking world-class industrial solutions or a fast-moving team to join, we are leading the way in tapping the true potential of live data.
Ready to unleash the future of AI? Let’s build the bleeding edge together.
Developer Platform Enhancement: Drive improvements to the core developer platform.
Agentic Solutions Building: Design and build agentic solutions for the platform, such as an "AI App Agent Builder".
End-to-End Deployment: Support robust inference pipelines, model serving architectures, and automated training/monitoring loops at scale.
Scalable Infrastructure: Command AWS resources (e.g., SageMaker, Bedrock) to scale AI workflows globally with maximum reliability.
Edge Processing: Provide occasional support for edge-hybrid deployment pipelines as needed, with a primary focus on core data processing systems.
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