Production Systems | Visual Intelligence | Real-World Signal Extraction

We build production-grade systems that extract reliable signal from messy, real-world visual data — systems trusted because they work consistently under real operating conditions, not because they look impressive in demos.

We are looking for a practical, production-minded Computer Vision Engineer who wants to build systems that create measurable operational impact.

This role carries real ownership, fast feedback loops, and the opportunity to work on systems deployed directly into live environments.

The Opportunity

You will work closely with domain experts, researchers, and engineers to build computer vision systems that:

extract actionable signal from video and image data

improve decision-making through proprietary data generation

create scalable, trusted operational intelligence

continuously improve through live feedback loops

turn unstructured visual information into measurable outcomes

You will own systems end-to-end, from problem framing, to ideation, execution and iteration.

What Makes This Role Different

We care about reliable systems, measurable outputs, and fast learning cycles.

You will operate with:

direct access to domain experts

high autonomy

tight operational feedback loops

minimal bureaucracy

This is an environment for builders who care more about useful systems than technical perfection.

What We're Looking For

You have already built systems that operate reliably in production environments.





You are comfortable working with:

imperfect or noisy visual data

ambiguous problem definitions

rapidly evolving requirements

quick iteration cycles

operationally critical systems

You move quickly, and are a practical thinker. You care about the outcomes and are likely stronger at shipping than presenting.

Technical Background

You will probably have strong experience across several of:

computer vision and image/video processing

Python and modern ML tooling

model training, evaluation, and deployment

production ML systems and infrastructure

monitoring, observability, and drift detection

dataset creation and labelling workflows

real-time or streaming data systems

experiment tracking and reproducibility

Experience working with production-grade data pipelines or operational AI systems is highly valuable.

We care more about judgement, execution speed, and production ownership than academic prestige.

What Success Looks Like

Within the first few months, we would expect:

production-ready CV systems deployed into live workflows

measurable improvements in signal quality and reliability

tighter iteration and feedback cycles

robust monitoring and retraining processes established

systems trusted by operators and stakeholders in production

Success in this role is measured by operational usefulness and system reliability.

Compensation

Compensation is flexible and designed to attract exceptional individuals.

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📌 Lead Computer Vision Engineer (New South Wales)
🏢 seek.com.au
📍 New South Wales