AI Research Engineer (Computer Vision & Imaging)

AI Research Engineer (Computer Vision & Imaging)

Imaging Research Full-time / Contract 3+ years experience

About Naicos

Naicos, a fast-paced startup, builds AI-native products for algorithmic commerce: the future of how e-commerce runs. Our first products are already live with paying customers, and we are shipping new ones continuously.

Your Role

You will drive the research behind our imaging products, finding approaches to hard, unsolved problems in product and apparel imagery that work at production scale. You will run the experiments, prove what is viable, and hand a working approach to the engineering team.

Who We Are Looking For

Total experience: 3 years or more, with a strong research orientation

Deep learning frameworks in Python: PyTorch or TensorFlow

Image processing in Python: OpenCV, Pillow, scikit-image

Working knowledge of diffusion and other image generation models

We are looking for a strong research or research-student profile: someone who investigates, experiments and proves an approach, working closely with the AI Architect. Someone who is driven to build solutions, not just desk research.

AI Skills and Experience

Computer vision: classical CV alongside deep learning.

Segmentation, image-to-image translation, geometry and lighting;

Generative imaging: diffusion models, conditioning and control, fine-tuning and LoRA,

Reads academic papers, judges what is reproducible, and turns one into a working prototype in days

Good to have

3D and rendering; published research or open-source contributions; model optimisation for inference cost

Research and innovative problem solving

Comfortable where there is no known answer, and defines the approach yourself

Solves problems inventively rather than reaching for the biggest model; many results come from classical image processing, fitment and geometric transformation

Other Relevant Skills and Experience

Designs experiments: baselines, measurable success criteria, honest reporting of negative results

Explains findings to a non-research audience and guides engineers to production

Git and reproducible experiment tracking (Weights & Biases, MLflow or similar)

Educational Qualification

BE / B.Tech / ME / M.Tech in Computer Science

BE / B.Tech / ME / M.Tech in any discipline with proven Computer Vision coursework or work

MSc / MS in Computer Science, Maths, Statistics or Computer Vision

PhD in Computer Vision or Machine Learning: an advantage, not a requirement

Reputed Tier 1 university preferred .