AI/ML Engineer (Computer Vision)

About Sigmawave AI

Most Vision AI systems don’t struggle because of weak models. They struggle because the right data is hard to get.

Rare events are unpredictable. Labelling is slow and expensive. Real-world footage is biased toward ideal conditions, while privacy and compliance limit how far teams can scale. The result? Models that look good in testing but break down in the field.

Sigmawave solves this at the data layer.

We scale 3D worlds to generate high-fidelity visual synthetic data, so teams can intentionally create the scenarios their models need to perform in the real world. From edge cases and rare threats to challenging lighting, weather, camera angles, and occlusion, our Synthetic Reality approach delivers coverage that real data can’t.

For video intelligence in security and public safety, this means faster iteration, reliable ground truth, and models that are trained to handle real-world complexity without waiting, compromising on privacy, or guessing where the gaps are.

Sigmawave turns data bottlenecks into deployment advantage.

Engineer the reality. Perfect the vision AI.

Company Overview

Sigmawave AI is a visual synthetic data company helping organisations build better computer vision and AI systems. We provide configurable, high-quality synthetic datasets that support model training, testing, and validation—delivered safely, efficiently, and at scale.

Job Description

We are seeking a Computer Vision AI Engineer to own the end-to-end delivery of real-world, high-performance video intelligence systems. In this role, you will architect, build, and optimize CV solutions that process live CCTV streams at scale. You will bridge the gap between research and production—designing the approach, building and training models (including the strategic use of synthetic data), and critically, optimizing every layer of the pipeline for maximum throughput and minimum latency.

You will own the full stack: from video decoding and streaming protocols (RTSP, HLS) to model inference (YOLO, PyTorch, TensorRT) and final integration with web platforms. If a stream lags, you will diagnose the codec. If GPU memory limits are hit, you will evaluate hardware alternatives or optimize further. If synthetic training data fails to generalize, you will measure the domain gap and implement solutions. This role is for an engineer who thrives on making CV systems robust, scalable, and production-ready.

Responsibilities

• Solution Architecture & Project Execution
• Model Development, Training & Synthetic Data Integration
• Inference Optimization & Scalable Deployment
• Cross-Functional Collaboration
• Required Qualifications
• Nice to have

What We Offer

• High ownership over challenging, real-world CV problems with tangible impact.
• Opportunity to architect solutions from the ground up and see them deployed at scale.
• A collaborative environment where you'll work alongside 3D artists, synthetic data engineers, and web/platform teams.
• Competitive compensation (commensurate with experience).
• Flexible working arrangements (subject to team needs).

How to Apply

Email hr@sigmawave.ai with:

• Your CV/resume
• Links to GitHub/portfolio and relevant demos (scene understanding, 3D reconstruction, generative pipelines, agentic systems)
• A short note describing 1–2 similar systems you’ve built and what you owned end-to-end

Email subject: Application - Computer Vision AI Engineer

Reference: SWA-CV-AIENGINEER-003

Location: Vietnam

Skills: Computer Vision, AI, CV Engineer, YOLO, PyTorch, TensorRT