Computer Vision

Advanced computer vision solutions designed for security, healthcare, and intelligent visual analysis.

– Computer Vision Services

Helping Businesses See More and Act Faster

Our computer vision services help organisations unlock value from visual data. By applying advanced image and video analysis, we support better security, smoother operations, and higher productivity. From object tracking to motion analysis, our solutions turn visual information into practical outcomes.

– Intelligent Computer Vision Solutions

Built for Automation and Real-World Use

Object Detection

Our object detection solutions accurately identify and locate objects within images and video streams. Using modern computer vision techniques, we process large volumes of visual data quickly and reliably.

Facial Recognition

We develop facial recognition systems that enable secure and accurate identity verification. These solutions support use cases across security, access control, marketing, and public safety.

Image Segmentation

Image segmentation divides visual data into meaningful regions. This makes it easier to analyse complex scenes, extract important details, and support advanced image-processing tasks.

Optical Character Recognition (OCR)

Our OCR solutions extract text from images, scanned documents, and video frames. Using deep learning, we convert visual content into structured, machinereadable data.

Scene Reconstruction

Scene reconstruction creates detailed 3D representations of real-world environments using visual inputs. This technology supports applications such as simulations, virtual reality, and spatial analysis.

Video Analysis

Our video analytics solutions analyse video streams to detect patterns, movements, and behaviours. This includes tracking people or objects and identifying key events in real time.

Benefits of Computer Vision

Our team is fully prepared to meet your needs and exceed your expectations.

 

High Accuracy

Computer vision models precisely detect, classify, and track objects in images and videos across multiple use cases.

Scalable Architecture

Our solutions scale from small image datasets to large, continuous video streams without compromising performance.

Flexible Configuration

We tailor data processing, algorithms, and output formats to meet specific business requirements.

Improved Public Safety

Real-time visual analysis helps identify activities and situations that enhance safety and situational awareness.

Top Computer Vision Platform We Use

We use industry-leading computer vision platforms and frameworks to deliver reliable and future-ready solutions.

– From Visual Data to Deployment

Computer Vision Development Process

Our engineer selection and hiring process involves identifying the necessary skills, experience, and cultural fit for the role, as well as assessing candidates’ problem-solving and collaboration abilities.

– Step 1

Data Collection and Preparation

We gather relevant visual data and prepare it through labelling, cleaning, and augmentation to ensure quality training inputs.

–  Step 2

Model Design

Our engineers select suitable deep learning architectures and fine-tune parameters to match the problem and performance goals.

– Step 3

Training and Evaluation

Models are trained on prepared datasets and evaluated against benchmarks to ensure accuracy and robustness.

– Step 4

Deployment

The final model is integrated into production systems, where it processes new visual data and delivers consistent, reliable results.

Contact us for more information and a free quotation

Job Description

Job Title: AI Engineer (Systems and Automation)
Location: On-site + Remote (Hybrid Australia)

About the Role

We are looking for an AI Engineer (Systems and Automation) who can build, deploy, and maintain robust AI systems while also designing automation solutions that streamline operations, product workflows, and decision-making. This role blends hands-on engineering, scalable system design, and practical automation using modern AI and MLOps practices.

Key Responsibilities:

AI Systems Engineering

  • Design, develop, and deploy end-to-end AI solutions—from prototype to production.
  • Build scalable, reliable ML pipelines for data ingestion, training, evaluation, and inference.
  • Implement monitoring for model performance, drift, latency, and reliability.
  • Optimize models and infrastructure for cost, speed, and accuracy.
  • Ensure security, privacy, and compliance across AI systems.

 

AI Automation Engineering

  • Identify business and technical processes that can be automated using AI.
  • Build AI-powered automation workflows using APIs, agents, orchestration tools, and event-driven architectures.
  • Develop integrations with internal tools (CRM, ERP, HRIS, support platforms, analytics stacks).
  • Create reusable components and templates to accelerate automation delivery.
  • Measure and report automation impact using clear KPIs.

 

Cross-Functional Delivery

  • Collaborate with Product, Data, Engineering, and Operations to scope and deliver AI initiatives.
  • Translate business needs into technical solutions with pragmatic trade-offs.
  • Document architectures, workflows, and operational runbooks.

 

Required Qualifications

  • 2–3+ years of experience in AI/ML engineering, automation engineering, or adjacent software roles.
  • Strong programming skills in Python (required); familiarity with TypeScript/Node.js is a plus.
  • Experience with model development using frameworks such as PyTorch, TensorFlow, or similar.
  • Solid understanding of the ML lifecycle, including feature engineering, training, evaluation, deployment, and monitoring.
  • Hands-on experience with MLOps practices and tools (CI/CD for ML, model registries, experiment tracking).
  • Experience integrating LLMs into real products or workflows (prompting, RAG, fine-tuning awareness, guardrails).
  • Strong system design skills and comfort working in cloud environments (AWS, GCP, or Azure).
  • Ability to troubleshoot production issues across data, model, and infrastructure layers.

 

Education

  • MS or BS in Artificial Intelligence, Machine Learning, Computer Science, Software Engineering, or a similar program.

 

Core Technical Skills

  • Data pipelines and orchestration (Airflow, Prefect, Dagster, or equivalents).
  • Serving and deployment (Docker, Kubernetes, serverless, REST/gRPC).
  • Observability and monitoring (logs, metrics, tracing; model drift and performance dashboards).
  • Datastores for AI workloads (SQL/NoSQL, vector databases).
  • API design and integration patterns.
  • Familiarity with responsible AI practices, evaluation frameworks, and safety controls.

 

Good to Have

  • AI research experience demonstrated through:
    • Publications, preprints, or thesis work.
    • Applied research projects in industry labs.
    • Contributions to open-source AI libraries.
  • Experience with multi-agent systems, tool-using LLMs, or advanced RAG architectures.
  • Experience in process automation platforms or iPaaS tools.
  • Exposure to regulated or high-compliance environments.

 

What Success Looks Like

  • Delivery of production-grade AI systems that are observable, reliable, and cost-efficient.
  • Implementation of automation opportunities that measurably reduce cycle time or operational load.
  • Contribution to best practices for AI governance, deployment, and lifecycle management.

 

What We Offer

  • Competitive compensation and benefits.
  • A high-ownership environment with real-world AI impact.
  • Opportunities to shape AI architecture, automation strategy, and engineering standards.

 

Equal Opportunity

We are an equal opportunity employer and value diversity in backgrounds, experiences, and perspectives.

Special Note: Agencies not applicable
Salary Range: $80K + Super