ML/AI Engineer
Indexed description
Our client is a fast-growing AI technology company that is building next-generation computer vision and edge AI solutions for large-scale real-world environments across global markets.
With deployments already spanning Asia, Europe, and North America, the team is focused on solving operational challenges through practical AI applications that combine machine learning, edge computing, and intelligent automation.
This is an opportunity to join a highly technical and fast-moving engineering team where you will play a key role in taking AI solutions from experimentation into production-scale deployment.
They are looking for an experienced ML Engineer with strong computer vision expertise to help design, train, optimise, and deploy AI models used in real-world environments.
This role goes beyond pure model training - you will work closely with engineering and product teams to improve system decision-making, validate model performance, and ensure production readiness across complex operational scenarios.
What you will do:
- Develop and improve computer vision and deep learning models for production applications
- Work on detection, tracking, and re-identification related tasks
- Build reliable evaluation, benchmarking, and validation workflows
- Optimise model performance for real-world deployment environments
- Collaborate with backend, platform, and product teams to integrate AI capabilities into production systems
- Analyse model performance, troubleshoot issues, and improve system reliability
- Contribute to tooling, experimentation pipelines, and technical decision-making
- Support continuous iteration through data-driven experimentation and validation
What you will need:
- Object Detection
- Multi-object Tracking
- Re-Identification
- Strong understanding of model evaluation methodologies and CV metrics
- Experience exporting and validating models using ONNX or similar frameworks
- Comfortable troubleshooting model, data, or inference-related issues
- Ability to work across both ML research and engineering implementation
- Comfortable using AI-assisted development tools effectively
- Good English communication skills for collaboration with international teams
Nice-to-haves:
- Experience with Vision-Language Models (VLMs)
- Video-based or multi-camera AI systems
- OpenVINO optimisation and quantisation (FP16 / INT8)
- Real-world AI deployment experience in industries such as retail, manufacturing, or smart environments
- Experience maintaining ML evaluation or benchmarking pipelines
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