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🤖 Data, AI & ML Engineers

Hire Dedicated Computer Vision Engineers — India, US, UK & Australia

Hire pre-vetted computer vision engineers who build systems that detect, classify, and interpret images and video in production. Golonex places dedicated India-based CV engineers with US, UK, Australian, and Indian teams — working in your timezone, under NDA, integrated within one week and with no lock-in.

The role

What a Computer Vision Engineer does

A computer vision engineer builds the models and pipelines behind image and video understanding: object detection, segmentation, OCR, pose estimation, and tracking. Our engineers work fluently with OpenCV, PyTorch, and detection frameworks like YOLO and Detectron2, handling data annotation, training, edge deployment, and inference optimisation for real-time performance.

Core expertise

Computer Vision OpenCV PyTorch & TensorFlow Object detection (YOLO, Detectron2) Image segmentation OCR Image classification (CNNs) Pose estimation & tracking Vision transformers (ViT) Data annotation pipelines Model optimisation (ONNX, TensorRT) Edge deployment Python Video analytics
Outcomes

What a Golonex Computer Vision Engineer builds for you

Object detection and recognition systems for images and video
Image segmentation and classification pipelines
OCR and document-digitisation engines
Real-time video analytics and tracking systems
Quality-inspection and defect-detection models
Edge-deployed vision models optimised for on-device inference
Engagement

How it works

Engagement models

Full-time dedicated Part-time / hourly Remote Hybrid Onsite (US · UK · India)

Based in India, working in your timezone. Onsite options available across the US, UK, and India.

Category

🤖

Data, AI & ML Engineers

Demand: Medium demand
Why Golonex for Computer Vision Engineers

The Golonex difference

Named, pre-vetted engineers

Every Computer Vision Engineer is screened for technical depth, communication, and reliability before you meet them — a sub-30% pass rate at the technical stage.

Integrated within 1 week

From enquiry to working team member in 5 business days. We handle onboarding, NDA, and access logistics.

Your timezone

India-based talent working overlapping hours with US, UK, and Australian teams. Daily standups and real-time collaboration, agreed upfront.

NDA-protected, no lock-in

Full IP and confidentiality protection as standard. Month-to-month engagements — scale up or down as your project evolves.

FAQ

Hiring a Computer Vision Engineer — FAQs

How quickly can I hire a computer vision engineer through Golonex? +

Usually within one week. We shortlist pre-vetted CV engineers matched to your problem — detection, segmentation, or OCR — you interview them, and the selected engineer is onboarded to your tools within 5 business days.

Do your computer vision engineers work in my timezone? +

Yes. Our engineers are India-based but work overlapping hours with US, UK, and Australian teams. The overlap window is agreed before the engagement so reviews and pairing happen in real time.

Can they deploy vision models to edge devices? +

Yes. Our engineers optimise and deploy models to edge hardware using ONNX and TensorRT, balancing accuracy against latency and memory. They handle everything from training on the cloud to running efficiently on cameras, mobile, or embedded devices.

Do they handle data annotation and dataset preparation? +

Yes. A large part of CV work is data — our engineers set up annotation workflows, augmentation, and quality checks, and can work with your existing labelled data or bootstrap a dataset. All data is handled under NDA.

How do you vet computer vision engineers? +

Every candidate passes a technical assessment on real vision scenarios plus an architecture review, a communication and remote-working assessment, and reference checks from at least two prior engagements. Our technical pass rate is under 30 percent.

Get started

Ready to hire a Computer Vision Engineer?

Tell us the role, stack, and timeline. We'll match you with a named, pre-vetted engineer — integrated within 1 week.