AI role · Open offer

Computer Vision Engineer — visual search

ViSenze

Full-time
Senior
Vision platform
Hybrid
71 Ayer Rajah Crescent, Singapore, SG 139951, Singapore · Hybrid
Singapore, Singapore
SGD 100k–150k/year + equity

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

4 skills2 tools

At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: 71 Ayer Rajah Crescent, Singapore, SG 139951, Singapore · Hybrid
Compensation: SGD 100k–150k/year + equity
Experience level: Senior
Team: Vision platform
Benefits & perks

About this role

What the team is looking for and how this position fits.

ViSenze is hiring a Senior Computer Vision Engineer — visual search on the Vision platform team (Hybrid · Singapore, Singapore). This is a hands-on role in computer vision & geospatial AI—not a generic “AI enthusiast” post.

You will own vision, sensor, or geospatial models in production end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

ViSenze builds visual search and image recognition for global retailers from one-north, Singapore.

Computer Vision Engineer: embeddings, multimodal retrieval, and latency-optimized serving.

Missions

Improve visual search quality on fashion and home catalogs.
Benchmark models on client SLA latency budgets.

Stack & environment

Python, PyTorch, Computer Vision, Kubernetes.

What we look for

CV production experience; hybrid Singapore.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
Computer Vision

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Visual search, embedding models, or multimodal retrieval at scale.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, Computer Vision, Machine Learning, and Kubernetes.
You have owned vision, sensor, or geospatial models in production in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Singapore, Singapore)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.

Apply

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Visual search, embedding models, or multimodal retrieval at scale.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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